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This study aims development of a neural network model to predict the signal amplitudes of diffusion MR signals of prostate tissues at high b-values from the amplitudes of low b-values obtained by using diffusion weighted imaging. Synthetic diffusion MR signals are generated using a kurtosis model for noise-free and noisy conditions considering nine b-values: the low b-values are 0, 50, 250, 500, 750s/mm2 and the high b-values are 1000, 1250, 1500, 2000s/mm2. Four radial basis functions neural networks (RBF-NN) connected in parallel are designed to accept the signal amplitudes at low b-values and to provide signal amplitudes at the high b-values. RBF-NNs housing altered number of neurons with radial basis functions attributing different widths in the hidden layers of the networks are analyzed. Learning and prediction performances of the NNs are assessed from training and testing datasets. For the noise-free condition, RBF-NNs reveal perfect predictions (r= 1.000) with very good learnings (MSE= 0.76-0.02×10-6). For the noisy conditions, the RBF-NNs achieve moderate to strong predictions (r= 0.981-0.463) with good learnings (MSE= 0.32-10.33×10-3). Prediction performance reduces as the level of noise and/or targeted high b-value increases. RBF-NNs facilitate prediction of high b-value diffusion MR signals of the prostate by requiring no diffusion signal decay function, optimization algorithm or initial/boundary values for the optimization algorithm. They may be quite functional in accurate voxel-wise generation of high b-value MR images for early detection and diagnosis of prostate cancer. Further prospective studies are needed to justify the potential benefits in clinical practice.

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

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 (? = 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. © 2020, Springer Science+Business Media, LLC, part of Springer Nature.

DOI: 10.26650/electrica.2018.97856Melanocytic lesions are the main cause ofdeath from skin cancer, and early diagnosis is the key to decreasing themortality rate. This study assesses the role of input-vector encoding in neuralnetwork-based classification of melanocytic lesions in dermoscopy. Twelvedermoscopic measures from 200 melanocytic lesions are encoded by compactencoding, adrenocortical dysplasia (ACD) encoding, 1-of-N encoding, normalizedencoding, and raw encoding, resulting in five different input-vector sets.Feed-forward neural networks with one hidden layer and one output layer aredesigned with several neurons in the hidden layer, ranging from two totwenty-two for each type of input-vector set, to classify a melanocytic lesioninto common nevus, atypical nevus, and melanoma. Accordingly, 105 networks aredesigned and trained using supervised learning and then tested by performing a 10-foldcross validation. All the neural networks achieve high sensitivities,specificities, and accuracies in classification. However, the network withseven neurons in the hidden layer and raw encoded dermoscopic measures as theinput vector realizes the highest sensitivity (97.0%), specificity (98.1%), andaccuracy (98.0%). The practical use of the network can facilitate lesionclassification by retaining the needed expertise and minimizing diagnosticvariability among dermatologists., DOI: 10.26650/electrica.2018.97856Melanocytic lesions are the main cause of death from skin cancer, and early diagnosis is the key to decreasing the mortality rate. This study assesses the role of input-vector encoding in neural network-based classification of melanocytic lesions in dermoscopy. Twelve dermoscopic measures from 200 melanocytic lesions are encoded by compact encoding, adrenocortical dysplasia (ACD) encoding, 1-of-N encoding, normalized encoding, and raw encoding, resulting in five different input-vector sets. Feed-forward neural networks with one hidden layer and one output layer are designed with several neurons in the hidden layer, ranging from two to twenty-two for each type of input-vector set, to classify a melanocytic lesion into common nevus, atypical nevus, and melanoma. Accordingly, 105 networks are designed and trained using supervised learning and then tested by performing a 10-fold cross validation. All the neural networks achieve high sensitivities, specificities, and accuracies in classification. However, the network with seven neurons in the hidden layer and raw encoded dermoscopic measures as the input vector realizes the highest sensitivity (97.0%), specificity (98.1%), and accuracy (98.0%). The practical use of the network can facilitate lesion classification by retaining the needed expertise and minimizing diagnostic variability among dermatologists.

The aim of this article is to facilitate the estimation of the distributed diffusion coefficient (DDC) of breast tissue in quantitative diffusion-weighted imaging using artificial neural networks. Diffusion signals of breast lesions and of healthy glandular tissue of contralateral breasts from 174 women measured on diffusion-weighted images captured with a 3T MR scanner using small region of interests were used. Traditional DDC estimates were obtained by a stretched exponential model and nonlinear least-squares fitting applied to the diffusion signals. Various multilayer perceptrons having one hidden layer but with different number of neurons were developed. Diffusion signals normalized and DDCs estimated traditionally were the input vectors and the target outputs of the neural networks, respectively, that were randomly divided into training, validation and test datasets. Supervised leanings were performed with the training and the validation datasets using a backpropagation algorithm followed by tests with the test dataset. DDC estimation by least-squares fitting takes 38 ms, on average. Strong positive correlations are observable between the DDC estimates by least-squares fitting and by the neural networks (overall r = 0.962–0.999). However, a network having seventeen neurons in its hidden layer provides the strongest correlation (r = 1.000). Once the learning of the network is accomplished, the network computes a DDC estimate only in 73 µs without requiring any initial value or any boundary constraint. Multilayer perceptrons facilitate the estimation of the distributed diffusion coefficient of breast tissue in diffusion-weighted imaging by offering less computational complexity and reduced computation time compared to nonlinear least-squares fitting. © 2018, Springer-Verlag GmbH Germany, part of Springer Nature.

The respiration pattern represents the volume of air in the lungs as afunction of time during human respiration process. Abnormal changes in thispattern can be signs of several diseases or conditions. There exit severalrespiration pattern detection methods. Among them, an easy technique relies onsensing the movements of thoracic and (or) abdominal regions. In this study, adevice based on thoracic motion tracking with complementary filtering has beendeveloped to detect the respiration pattern. The device is equipped with a motionsensor placed in a flexible belt housing a three-axis accelerometer and a three-axisgyroscope and a UART-to-USB converter providing computer connectivity. Thedevice is operated by a microcontroller that controls the operation of the motionsensor, applies complementary filtering to the motion data acquired and transfersthe results to a personal computer. The device is powered from the computer it isconnected to. Experiments with using the device during continues inhaling andexhaling, deep inhaling followed by breath-hold and deep exhaling followed bybreath-hold respiration activities in standing, lying and seated postures show thatthoracic motion tracking with complementary filtering may provide quite wellrespiration pattern detections. Solunum motifi, insan solunum işlemi sırasında zamanın bir fonksiyonuolarak akciğerlerdeki hava hacmini temsil eder. Bu desendeki anormaldeğişiklikler birtakım hastalıkların veya durumların belirtileri olabilir. Solunummotifinin tespitinde birçok yöntem bulunmaktadır. Bunlar arasında kolay birteknik göğüs ve (veya) karın bölgelerinin hareketlerinin algılanmasınadayanmaktadır. Bu çalışmada, tamamlayıcı filtreleme ile göğüs hareket izlemeyedayalı bir solunum deseni tespit cihazı geliştirilmiş bulunmaktadır. Cihaz esnek birkemer içine yerleştirilmiş üç eksenli bir ivmeölçer ve üç eksenli bir jiroskopbarındıran bir hareket algılayıcısı ve bilgisayar bağlantısı sağlayan bir UART-USBdönüştürücüsü ile donatılmıştır. Cihaz hareket algılayıcısının çalışmasını kontroleden, elde edilen hareket verilerine tamamlayıcı filtreleme uygulayan ve sonuçlarıkişisel bir bilgisayara aktaran bir mikrodenetleyici tarafından işletilmektedir.Cihaz bağlı olduğu bilgisayardan beslenmektedir. Ayakta durma, yatma ve oturmapozisyonlarında; sürekli nefes alma ve verme, derin nefes almayı takiben nefestutma ve derin nefes vermeyi takiben nefes tutma solunum aktiviteleri süresincecihaz kullanarak gerçekleştirilen deneyler tamamlayıcı filtreleme ile göğüshareketi izlemenin oldukça iyi solunum deseni tespitlerine imkân tanıyabildiğinigöstermektedir.

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 (rMD(min)) show the same highest correlation with GS (both rho = -0.73). Between 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., NA

Advanced smart pillboxes are needed for use with the heart rate regulating drugs. The most important component of these pillboxes is the heart beat rate sensor. In this study, experimental analyses have been performed with different optical sensors namely HRM-2511B transmissive sensor, TCRT1000 reflective sensor and PulseSensor reflective sensor in heartbeat sensing. All of the sensors provide very similar frequency signals captured from the left index finger. All the sensors give quite similar and correct measurement results when compared with the reference device. However, the measurement consistency is highly dependent on the placement of the fingertip on the sensor. TCRT1000 and PulseSensor sensors require additional mechanical setup while HRM-2511B sensor is already equipped with a robust fingertip fixing mechanism. In the future, we are planning to develop an advanced smart pillbox based on the HRM-2511B sensor. © 2017 IEEE. 2017 Medical Technologies National Conference, TIPTEKNO 2017 -- 12 October 2017 through 14 October 2017 -- -- 134046

Reflective optical SpO2/Heartbeat sensors are very popular nowadays due to their ability to be used in different body regions that makes many different innovative designs possible. However, performance tests and evaluations are needed to obtain reliable and stable measurement results from these sensors. In this study, the performance of such a sensor, namely MAX30100 SpO2/Heartbeat sensor, has been assessed by performing measurement trials. SpO2 and heartbeat measurements were performed from the index finger, forehead and temporal bone. During measurements, a constant value of 50mA applied to the infrared LED in the sensor while the current value for the red LED was changed between 4,4mA and 20,8mA in discrete time intervals. Reference measurements were taken with a pulse oximeter from the right index finger simultaneously during all measurements. The findings show that the 14.2mA red LED current value provides similar results with the reference device. The measurements taken from the forehead and temporal bones are acceptable when compared to the measurements taken with the reference device. We plan to develop a wearable device equipped with MAX30100 sensor that will automatically determine the most suitable red LED current value depending on the skin color and thickness and that can perform measurements during basic daily activities. © 2017 IEEE. 2017 Medical Technologies National Conference, TIPTEKNO 2017 -- 12 October 2017 through 14 October 2017 -- -- 134046

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 0.05). 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.

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).

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 (R 2 adj = 0.55–0.60, AUC = 0.88–0.91), however the models using the measure ratios perform better (R 2 adj = 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. © 2018

The most important problem encountered in Functional Near Infrared Spectroscopy is the loss of stability and reliability of the light emitting diode as a result of an on going heat transfer between the living tissue and the light emitting diode. This condition has an unwanted disruptive effect on the radiated light. Within this study, a current source circuit with temperature feedback is developed to reduce these effects to minimum and preliminary experiments are done with the developed circuit. The developed circuit is an op-amp based constant current source which consists of a digital potentiometer, a temperature sensor and a microcontroller. Regarding the temperature reading, microcontroller manipulates the value of the digital potentiometer, thereby manipulating the current supplied to the light emittng diode by the current source, instantly. Preliminary studies showed that, the circuit developed for operation between 20°C and 46°C temperature values is much more beneficial when compared to a simple current source. In future, manufacturing the circuit in a modular structure is planned for clinical applications. © 2017 IEEE. 21st National Biomedical Engineering Meeting, BIYOMUT 2017 -- 24 November 2017 through 26 November 2017 -- -- 140363

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/mm(2)), lower b-value images (ADC low; b=50 and 400s/mm2) and higher b-value images (ADC(high); b=400 and 800s/mm(2)). A set of dual-phase ADC (dpADC) models were constructed using ADC low, ADC high and a perfusion influence factor ranging from 0 to 1. Results: Strong positive correlation is observable between ADC and all dpADCs (rho=0.80-1.00). Differences in ADC and dpADCs between the benign and the malignant lesions are all significant (p

Reflective optical SpO 2 /Heartbeat sensors are very popular nowadays due to their ability to be used in different body regions that makes many different innovative designs possible. However, performance tests and evaluations are needed to obtain reliable and stable measurement results from these sensors. In this study, the performance of such a sensor, namely MAX30100 SpO 2 /Heartbeat sensor, has been assessed by performing measurement trials. SpO2 and heartbeat measurements were performed from the index finger, forehead and temporal bone. During measurements, a constant value of 50mA applied to the infrared LED in the sensor while the current value for the red LED was changed between 4,4mA and 20,8mA in discrete time intervals. Reference measurements were taken with a pulse oximeter from the right index finger simultaneously during all measurements. The findings show that the 14.2mA red LED current value provides similar results with the reference device. The measurements taken from the forehead and temporal bones are acceptable when compared to the measurements taken with the reference device. We plan to develop a wearable device equipped with MAX30100 sensor that will automatically determine the most suitable red LED current value depending on the skin color and thickness and that can perform measurements during basic daily activities.

Advanced smart pillboxes are needed for use with the heart rate regulating drugs. The most important component of these pillboxes is the heart beat rate sensor. In this study, experimental analyses have been performed with different optical sensors namely HRM-2511B transmissive sensor, TCRT1000 reflective sensor and PulseSensor reflective sensor in heartbeat sensing. All of the sensors provide very similar frequency signals captured from the left index finger. All the sensors give quite similar and correct measurement results when compared with the reference device. However, the measurement consistency is highly dependent on the placement of the fingertip on the sensor. TCRT1000 and PulseSensor sensors require additional mechanical setup while HRM-2511B sensor is already equipped with a robust fingertip fixing mechanism. In the future, we are planning to develop an advanced smart pillbox based on the HRM-2511B sensor.

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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.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, 1.90NLR ≤2.93; group 3, NLR2.93).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 (p0.001, 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 (p0.001, 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 p0.001). 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).The NLR is a useful parameter to assess postoperative in-hospital mortality risk after valvular surgery.

Change in urine color is due to several diseases or metabolic activity. Detection of the urine color change and diagnosis of the color change related diseases are performed at the hospitals after several comprehensive tests. In this study, a urine color detecting device, which can be used at home healthcare, has been developed. The device is equipped with a homogeneous light source and a power supply that supplies power to this source, a light intensity detecting sensor, a USB-to-Serial convertor module. The device is connected to a portable computer via this module and light intensity measurements are operated by a software run on the computer. Test performed using the device and real urine samples show that the device developed can provide quite beneficial urine color measurements in an accurate, reliable and sensitive manner. © 2015 IEEE. 19th National Biomedical Engineering Meeting, BIYOMUT 2015 -- 5 November 2015 through 6 November 2015 -- -- 118881

Background Postdilatation (PD) with noncompliant balloon during elective percutaneous coronary intervention (PCI) is performed usually in clinical practice in order to optimize stent expansion. However, current knowledge about its use in patients undergoing primary PCI is controversial. This study aims to evaluate the angiographical and clinical results of PD in patients who underwent primary PCI with drug eluting stents (DESs). Methods A total of 405 consecutive patients (mean age 56.9 ± 12.3 years; 302 male) with ST elevation myocardial infarction were evaluated retrospectively. Patients received DES with or without predilatation according to physician's discretion. Eligible patients were divided into 2 groups based on PD procedure. The clinical end-points were death, target vessel revascularization (TVR) and stent thrombosis at 6 months after PCI. The angiographic end-points were postprocedural correct Thrombolysis in Myocardial Infarction (TIMI) frame count (cTFC), final TIMI flow, and myocardial blush grade (MBG). Results PD was performed in 214 patients (52.8%). Angiographical parameters such as TIMI flow, cTFC, and MBG did not differ after PD (P > 0.05). During 6-month follow-up, TVR and stent thrombosis rates were lower in the PD group (6 vs. 16, P = 0.03; and 3 vs. 10, P = 0.04, respectively). PD and diabetes were detected as independent predictors of MACE (β = 0.52, P = 0.01, and β = −0.47, P = 0.02; respectively). Conclusion Our study revealed that PD does not yield adverse effects on final angiographic parameters when performed during primary PCI. Besides PD seems to decrease probability of stent thrombosis and TVR.

To investigate the effect of magnetic field heterogeneity in breast dynamic contrast-enhanced examinations with fat saturation (DCE-FS). The magnetic field was mapped over the breasts in ten patients. DCE-FS was undertaken at 1.5 T with fast spoiled gradient echoes and spectrally selective fat saturation. Signal intensity was calculated for T1 values 25–1,200 ms both on and off resonance, and results were verified with a test object. Clinical examinations were evaluated for the predicted effects of field heterogeneity. Magnetic field was found to vary by 3.6 ± 1.2 ppm over the central transaxial slice and 5.1 ± 1.5 over the whole breast volume (mean ± standard deviation). Computer simulations predict a reduction in the dynamic range if field heterogeneity leads to unintended water suppression, and distortion to CA uptake curves due to fat suppression failure (for fat containing pixels). A compromise between dynamic range and fat saturation performance is required. Both water suppression and fat suppression failure are apparent in clinical examinations. Magnetic field heterogeneity is likely to reduce the sensitivity of DCE-FS by distorting the CA uptake curves because of fat suppression failure (for fat containing pixels) and by reducing the dynamic range because of unintended water suppression. • Magnetic field heterogeneity is significant in breast magnetic resonance. • Contrast-agent uptake curves are distorted by a non-uniform magnetic field. • Radiologist must be aware of possibility of distortion to interpret uptake curves correctly. • Compromise between fat suppression and dynamic range is required.

In pulse oximeter devices, the most important issue is the generation of appropriate light intensity by the light source according to the color and the composition of the target tissue. For this purpose, these devices are equipped with dedicated driver circuits that transfer different levels of DC current levels to the LEDs acting as the light sources. The current level is typically ranging from 5mA to 20mA and automatically adjusted so as to increase gradually. In this study, three different transistor based and microcontroller-controlled DC current sources for use in pulse oximeter devices have been designed, simulation and practical implementations have been performed and results have been analyzed.

In this study, we introduce a novel, robust and accurate computerized algorithm based on volumetric principal component maps and template matching that facilitates lesion detection on dynamic contrast-enhanced MR. The study dataset comprises 24 204 contrast-enhanced breast MR images corresponding to 4034 axial slices from 47 women in the UK multi-centre study of MRI screening for breast cancer and categorized as high risk. The scans analysed here were performed on six different models of scanner from three commercial vendors, sited in 13 clinics around the UK. 1952 slices from this dataset, containing 15 benign and 13 malignant lesions, were used for training. The remaining 2082 slices, with 14 benign and 12 malignant lesions, were used for test purposes. To prevent false positives being detected from other tissues and regions of the body, breast volumes are segmented from pre-contrast images using a fast semi-automated algorithm. Principal component analysis is applied to the centred intensity vectors formed from the dynamic contrast-enhanced T1-weighted images of the segmented breasts, followed by automatic thresholding to eliminate fatty tissues and slowly enhancing normal parenchyma and a convolution and filtering process to minimize artefacts from moderately enhanced normal parenchyma and blood vessels. Finally, suspicious lesions are identified through a volumetric sixfold neighbourhood connectivity search and calculation of two morphological features: volume and volumetric eccentricity, to exclude highly enhanced blood vessels, nipples and normal parenchyma and to localize lesions. This provides satisfactory lesion localization. For a detection sensitivity of 100%, the overall false-positive detection rate of the system is 1.02/lesion, 1.17/case and 0.08/slice, comparing favourably with previous studies. This approach may facilitate detection of lesions in multi-centre and multi-instrument dynamic contrast-enhanced breast MR data. EPSRCEngineering & Physical Sciences Research Council (EPSRC) [E035736/1]; Cancer Research UKCancer Research UK; MRCMedical Research Council UK (MRC); Department of HealthDiabetes UK [C1060/A10334]; NHS; Engineering and Physical Sciences Research CouncilEngineering & Physical Sciences Research Council (EPSRC) [EP/J50077X/1, EP/E035736/1]; Medical Research CouncilMedical Research Council UK (MRC) [G0701533]; National Institute for Health ResearchNational Institute for Health Research (NIHR) [NF-SI-0512-10162] This work was supported by EPSRC (E035736/1) and also by Cancer Research UK and EPSRC with support from MRC and the Department of Health (C1060/A10334), together with support from NHS funding to the NIHR Biomedical Research Centre. We are grateful to the MARIBS study for providing data enabling us to evaluate this lesion localization method.

PubMed ID: 17854795 A novel fully automated system is introduced to facilitate lesion detection in dynamic contrast-enhanced, magnetic resonance mammography (DCE-MRM). The system extracts breast regions from pre-contrast images using a cellular neural network, generates normalized maximum intensity-time ratio (nMITR) maps and performs 3D template matching with three layers of 12 × 12 cells to detect lesions. A breast is considered to be properly segmented when relative overlap > 0.85 and misclassification rate < 0.10. Sensitivity, false-positive rate per slice and per lesion are used to assess detection performance. The system was tested with a dataset of 2064 breast MR images (344 slices × 6 acquisitions over time) from 19 women containing 39 marked lesions. Ninety-seven percent of the breasts were segmented properly and all the lesions were detected correctly (detection sensitivity = 100 %), however, there were some false-positive detections (31%/lesion, 10%/slice). © 2007 Elsevier Ltd. All rights reserved.

Cellular neural networks(CNNs) are massively parallel cellular structures with learning abilities. They can be used to realize complex image processing applications efficiently and in almost real time. In this preliminary study, we propose a novel, robust, and fully automated system based on CNNs to facilitate lesion localization in contrast-enhanced MRmammography, a difficult task requiring the processing of a large number of images with attention paid to minute details. The data set consists of 1170 slices containing one precontrast and five postcontrast bilateral axial MRmammograms from 39 patients with 37 malignant and 39 benign mass lesions acquired using a 1.5 Tesla MRscanner with the following parameters: 3D FLASH sequence, TR/TE 9.80/4.76 ms, flip angle 25 ° , slice thickness 2.5 mm, and 0.625 × 0.625 mm 2 in-plane resolution. Six hundred slices with 21 benign and 25 malignant lesions of this set are used for training the CNNs; the remaining data are used for test purposes. The breast region of interest is first segmented from precontrast images using four 2D CNNs connected in cascade, specially designed to minimize false detections due to muscles, heart, lungs, and thoracic cavity. To identify deceptively enhancing regions, a 3D nMITR map of the segmented breast is computed and converted into binary form. During this process tissues that have low degrees of enhancements are discarded. To boost lesions, this binary image is processed by a 3D CNN with a control template consisting of three layers of 11 × 11 cells and a fuzzy c -partitioning output function. A set of decision rules extracted empirically from the training data set based on volume and 3D eccentricity features is used to make final decisions and localize lesions. The segmentation algorithm performs well with high average precision, high true positive volume fraction, and low false positive volume fraction with an overall performance of 0.93 ± 0.05 , 0.96 ± 0.04 , and 0.03 ± 0.05 , respectively (training: 0.93 ± 0.04 , 0.94 ± 0.04 , and 0.02 ± 0.03 ; test: 0.93 ± 0.05 , 0.97 ± 0.03 , and 0.05 ± 0.06 ). The lesion detection performance of the system is quite satisfactory; for the training data set the maximum detection sensitivity is 100 % with false-positive detections of 0.28/lesion, 0.09/slice, and 0.65/case; for the test data set the maximum detection sensitivity is 97 % with false-positive detections of 0.43/lesion, 0.11/slice, and 0.68/case. On the average, for a detection sensitivity of 99 % , the overall performance of the system is 0.34/lesion, 0.10/slice, and 0.67/case. The system introduced does not require prior information concerning breast anatomy; it is robust and exceptionally effective for detecting breast lesions. The use of CNNs, fuzzy c -partitioning, volume, and 3D eccentricity criteria reduces false-positive detections due to artifacts caused by highly enhanced blood vessels, nipples, and normal parenchyma and artifacts from vascularized tissues in the chest wall due to oversegmentation. We hope that this system will facilitate breast examinations, improve the localization of lesions, and reduce unnecessary mastectomies, especially due to missed multicentric lesions and that almost real-time processing speeds achievable by direct hardware implementations will open up new clinical applications, such as making feasible quasi-automated MR-guided biopsies and acquisition of additional postcontrast lesion images to improve morphological characterizations.

Rationale and Objectives The objective of this work was to develop a quantitative method for improving lesion detection in dynamic contrast-enhanced magnetic resonance mammography (DCEMRM). For this purpose, we segmented and analyzed suspicious regions according to their contrast enhancement dynamics, generated a normalized maximum intensity–time ratio (nMITR) projection, and explored it to extract important features, to improve accuracy and reproducibility of detection. Materials and Methods A novel automated method is introduced to segment and analyze lesions in three dimensions. It consists of four consecutive stages: volume of interest selection, nMITR projection generation using a voxel sampling method based on a moving 3 × 3 mask, three-dimensional lesion segmentation, and feature extraction. The nMITR projection of the detected lesion is used to extract six features: mean, maximum, standard deviation, kurtosis, skewness, and entropy, and their diagnostic significance is studied in detail. High-resolution MR images of 52 breast masses from 46 women are analyzed using the technique developed. Results Entropy, standard deviation, and the maximum and mean value features were found to have high significance ( P Conclusion The lesion detection method described is efficient and leads to improved, accurate, reproducible diagnoses. It is reliable in terms of observer variability and may allow for a better standardization of clinical evaluations. The findings demonstrate the usefulness of nMITR based features; nMITR-entropy shows the best performance for quantitative diagnosis.

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).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.A stretched exponential model provides significantly better fits then the monoexponential model (P0.001): 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 (P0.05). 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.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.

In this study, a portable and programmable transcutaneous electrical nerve stimulation device providing a single channel and single-phase rectangular wave output has been developed. The device is equipped with a pair of carbon-rubber self-adhesive electrodes with a surface area of 5cm2. High amplitude stimulation pulses applied across the electrodes are produced by a transformer from the low-amplitude states. Select the desired frequency and notice period to the owners of single-phase stimulus of low amplitude waves where the software is produced by the microcontroller within the transformer driver circuit and the amplitude is set manually by using a variable resistor. The device provides wave outputs of 0-79 mA current range and 15Hz-250Hz frequency range. The device developed is operated with a 9V battery and offers a single-channel output. However, if required, it has a power socket allowing to connect to an external power adapter and it can be easily upgraded to provide two-channel outputs.

Administration of medicine through vessels is usually carried out using syringe pumps. In this study, a programmable electronic syringe pump and a computer software computer interface that ensures the effective use of the pump has been developed. The syringe pump developed has a mechanical structure, a servo motor, a microcontroller, a power supply stage and a PC connection module. Calibration of the pump is done by performing several experiments with a 5ml syringe to clarify the relationship of the wave pulse width required by the servo motor to provide the desired flow rate. Using computer software interface, the serial port which the pump is connected to is selected first. A list is created by entering the flow rate and the time. After each entry, total volume is automatically calculated. Once the list is completed, a simulation can be executed to visually inform the operator about the volume to be administered. Next,, administration process is started. Volume in the syringe is continually updated during administration. The process can be stopped immediately at any time by the operator. © 2015 IEEE. Medical Technologies National Conference, TIPTEKNO 2015 -- 15 October 2015 through 18 October 2015 -- -- 118954

In this study, relationship between the Hurst exponent and the Poincare parameters utilized in analysis of non-linear signals was investigated. A total of 800 artificial signals, composed of signals with eight different lengths and one hundred signals for each length, was produced using fractional Brownian motion signals. “Rescaled Range” analysis was performed to determine Hurst exponent and Poincare parameters were calculated by performing Poincare analysis to each signal. Pearson correlation analysis results show that there is no significant correlation between Poincare parameters and Hurst exponent. However, it should be noted that, in this study, artificial signals have been used. Analysis of actual signals will be the subject of our next study.

In this study, the files published on OSYM web site that consist of the lists of “Higher education degree programs accepting students via central placements” are inspected for a five-year period starting from the year of 2010. Considering the Biomedical engineering programs, universities, quotas and the number of students placed were noted. Using the data noted, several tables and graphs providing valuable information were generated and interpreted. A number of predictions were made for the year of 2020.

OBJECTIVES: Previous studies have demonstrated the role of inflammation in acute heart failure. The neutrophil-to-lymphocyte ratio was found to be a useful inflammatory marker for predicting adverse outcomes. We hypothesized that an elevated neutrophil-to-lymphocyte ratio would be associated with increased mortality in acute heart failure patients. METHODS: The study cohort consisted of 167 acute heart failure patients with an ejection fraction

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, cDWI 1500, cDWI 2000, and cDWI 3000 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 cDWI(3000) image set. cDWI(2000) 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. cDWI 2000 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., NA

Environmental temperature and humidity levels have impacts on organisms and therefore care is taken to measure/monitor and maintain them at certain levels in daily life. In this study, a portable multichannel temperature and humidity monitoring device has been developed. The device houses multiple temperature sensors, a humidity sensor, a microcontroller, a display and a +9V battery. Tests with three temperature sensors show that the device is user-friendly and performs consistent measurements. The device is able to operate thirty-six sensors at maximum and can transfer measurement results to any personal computer or Bluetooth device with universal asynchronous receiver input. © 2013 The Chamber of Turkish Electrical Engineers-Bursa. 8th International Conference on Electrical and Electronics Engineering, ELECO 2013 -- 28 November 2013 through 30 November 2013 -- Bursa -- 102644

Human body temperature is influenced by many factors such as cognitive, emotional and psychological states. Temperature measurements can be done using analogue or digital electrical sensors. High sensitivity and high accuracy in measurements are usually provided by the analogue sensors that require sophisticated circuits for linearization/calibration and also for digitization. When compared with the analogue ones, digital sensors can also provide high sensitivity but lower accuracy although good enough for several medical applications. In this study, a portable device with wireless computer connectivity that provides noninvasive dual channel digital body temperature measurements has been developed. Trials with the device show that it is quite beneficial in measuring body temperature from ear canal. It may also be used to perform temperature measurements from mouth, armpit and anus. © 2013 IEEE. 2013 10th International Conference on Electronics, Computer and Computation, ICECCO 2013 -- 7 November 2013 through 8 November 2013 -- Ankara -- 102696

The purpose of this study was to examine the influence of the lunar phases and lunar brightness on cardiac autonomic function (CAF) in healthy individuals. A total of 177 healthy individuals were included in the study. All individuals underwent 24h ambulatory electrocardiography (Holter monitoring). Four groups were used at different phases and brightnesses of the moon. Cardiac sympathetic and parasympathetic activity was assessed using heart rate variability (HRV). Time domain and spectral power analyses were used on the results obtained from Holter monitoring. Standard deviation of all R-R intervals (SDNN), standard deviation of the averages of R-R intervals in all 5-min segments of the entire recording (SDANN), SDNN index, the square root of the mean of the sum of the squares of differences between adjacent R-R intervals (RMSSD) and NN50 count divided by the total number of all NN intervals (pNN50) were obtained from the time-domain analyses. Spectral power analysis was used to estimate total power and very low frequency (VLF), low frequency (LF) and high frequency (HF) components. The results from time domain and spectral power analyses were divided into two groups for separately estimating cardiac sympathetic and parasympathetic activities when awake (06:00-22:00h) and asleep (22:00-06:00h). Results are presented as mean +/- SD, a p-value being considered significant if p

Postdilatation (PD) with noncompliant balloon during elective percutaneous coronary intervention (PCI) is performed usually in clinical practice in order to optimize stent expansion. However, current knowledge about its use in patients undergoing primary PCI is controversial. This study aims to evaluate the angiographical and clinical results of PD in patients who underwent primary PCI with drug eluting stents (DESs).A total of 405 consecutive patients (mean age 56.9 ± 12.3 years; 302 male) with ST elevation myocardial infarction were evaluated retrospectively. Patients received DES with or without predilatation according to physician's discretion. Eligible patients were divided into 2 groups based on PD procedure. The clinical end-points were death, target vessel revascularization (TVR) and stent thrombosis at 6 months after PCI. The angiographic end-points were postprocedural correct Thrombolysis in Myocardial Infarction (TIMI) frame count (cTFC), final TIMI flow, and myocardial blush grade (MBG).PD was performed in 214 patients (52.8%). Angiographical parameters such as TIMI flow, cTFC, and MBG did not differ after PD (P0.05). During 6-month follow-up, TVR and stent thrombosis rates were lower in the PD group (6 vs. 16, P=0.03; and 3 vs. 10, P=0.04, respectively). PD and diabetes were detected as independent predictors of MACE (β=0.52, P=0.01, and β=-0.47, P=0.02; respectively).Our study revealed that PD does not yield adverse effects on final angiographic parameters when performed during primary PCI. Besides PD seems to decrease probability of stent thrombosis and TVR.

Background: Acute heart failure (AHF) is a major cause of hospitalisation, morbidity and mortality worldwide. Gamma-glutamyl transferase (GGT) is an enzyme responsible for the extracellular catabolism of antioxidant glutathione and a potential risk indicator of cardiac mortality. Limited data exists on the prognostic value of circulating levels of GGT in patients hospitalized due to AHF. Aim: To study the association between baseline GGT activity and in-hospital mortality in AHF patients. Methods: The study cohort consisted of 183 AHF patients with left ventricular ejection fraction (LVEF) < 50%. The primary endpoint was in-hospital mortality. Patients were divided into two groups according to in-hospital mortality. The relationship between GGT activity and in-hospital mortality was tested using logistic regression models, adjusting for clinical characteristics and echocardiographic findings. Results: After adjustment for possible confounders, GGT level was significantly related (OR 1.056, 95% CI 1.018–1.096, p = 0.04) to in-hospital mortality. Conclusions: Elevated GGT activity is an independent predictor of short-term mortality in patients with AHF and reduced LVEF.

Introduction. Red cell distribution width (RDW) has been associated with poor outcomes in patients with cardiovascular diseases. However, little is known about the role of RDW in prediction of new-onset atrial fibrillation (AF) after coronary artery bypass grafting (CABG). We aimed to investigate the relation between the RDW and postoperative AF in patients undergoing CABG. Methods. A total of 132 patients undergoing nonemergency CABG were included in the study. Patients with previous atrial arrhythmia or requiring concomitant valve surgery were excluded. We retrospectively analyzed 132 consecutive patients (mean age, 60.55 +/- 9.5 years; 99 male and 33 female). The RDW level was determined preoperatively and on postoperative Day 1. Results. Preoperative RDW levels were significantly higher in patients who developed AF than in those who did not (13.9 +/- 1.4 vs. 13.3 +/- 1.2, p = 0.03). There was not any correlation between postoperative RDW levels and AF. Using a cutpoint of 13.45, the preoperative level correlated with the incidence of AF with a sensitivity of 61% and specificity of 60%. Conclusion. Preoperative RDW level predicts new-onset AF after CABG in patients without histories of AF.

Background Neutrophil/lymphocyte ratio (NLR) has been associated with poor outcomes in patients with cardiovascular diseases. However, little is known about the role of NLR in patients with thromboembolic stroke due to atrial fibrillation (AF). We aimed to compare the NLR ratios between non-valvular AF patients with or without thromboembolic stroke. Methods A total of 126 non-valvular AF patients with or without stroke were included in the study; 126 consecutive patients (52 males and 74 females), mean age, 70 ± 10.2 years old. No patient had a recent history of an acute infection or an inflammatory disease. Baseline NLR was measured by dividing neutrophil count to lymphocyte count. WBC count > 12.000 cells per μL or 38 o are excluded from the study. Results Mean NLR was significantly higher among persons with stroke compared to individuals without a stroke (5.6 ± 3.4 vs. 3.1 ± 2.1, p = 0.001). There were no significant differences in RDW levels between the two groups (p > 0.05). HAS-BLED and CHADS2 scores were significantly higher in the stroke group. Conclusion Higher NLR, an emerging marker of inflammation, is associated with thromboembolic stroke in non-valvular AF patients.

In rehabilitation of walking difficulties, it is vital to be aware of the distribution of the force and moment pairs faced by the lower limb extremities. The mathematical equations for numerical computation of these pairs are provided by free body diagrams that require some foot force measurements and joint/segment-tilt angle measurements as well. In this study, a device has been developed to capture the foot force and the ankle, knee and hip joint angles. The device is equipped with three accelerometers and six force sensitive resistors. The measured forces and angles are computed and next transferred to personal computer. The device is calibrated and then tested on a healthy volunteer. The test results show that the device may be used to provide valuable measurements to compute force distributions in lower extremity. © 2013 The Chamber of Turkish Electrical Engineers-Bursa. 8th International Conference on Electrical and Electronics Engineering, ELECO 2013 -- 28 November 2013 through 30 November 2013 -- Bursa -- 102644

Background: Presence of Metabolic Syndrome (MetS) has been shown to predict higher risk for cardiovascular diseases. However, in patients with ST Segment Elevation Myocardial Infarction (STEMI), prognostic importance of MetS has not been widely studied. Methods: We prospectively recruited 611 STEMI patients (521 male, 90 female) who were treated by primary angioplasty. Metabolic syndrome was diagnosed according to the International Diabetes Federation metabolic syndrome worldwide definition. Coronary angiographic data and in-hospital events of individuals were recorded. Major Adverse Cardiac Events (MACE) included cardiac death, recurrent myocardial infarction and target lesion revascularization. Results: Metabolic syndrome group included 276 (45.1% of the study cohort; mean age 56.8 ± 12.2; 210 male) and control group included 335 subjects (54.9% of the study cohort; mean age 55.6 ± 12.9; 311 male). The frequency of female gender, hypertension, Diabetes Mellitus (DM), hyperlipidemia and positive history for coronary artery disease were higher in MetS group, whereas, the ratio of smokers was higher in the control group. The incidence of in-hospital death and MACE was not statistically different in MetS and control groups. Presence of MetS was not correlated with in-hospital death and MACE in univariate analysis. In multivariate analysis using model adjusted for age, gender, DM/ fasting glucose >100 mg/dL, left ventricular ejection fraction, post-PCI TIMI flow grade

WOS: 000313642600007, PubMed: 22334879, The impact of coronary revascularization methods (coronary artery bypass graft [CABG] surgery and stent implantation) on clinical outcome has not been determined yet in patients with systolic heart failure (SHF). We examined outcomes in patients discharged from our hospital after hospitalization for decompensated SHF. Of 637 patients with SHF (mean age, 64 +/- 13 years; mean ejection fraction, 26.5% +/- 9%), 402 patients (63%) had coronary artery disease (CAD) and 235 patients (37%) had no CAD; 223 patients (35%) died because of cardiovascular reasons during follow-up. Patients who had stenting alone and patients who had CABG surgery and stenting had better prognosis than patients with CAD but no revascularization procedure (P < .001 and P = .013, respectively). In the patients with SHF having CAD who had stenting and CABG surgery + stenting may have better prognosis compared with patients with CAD who had no revascularization procedure in their past.

OBJECTIVES We aimed to examine in-hospital and long-term outcomes of red blood cell (RBC) transfusions in patients undergoing a primary percutaneous coronary intervention (PCI) for ST-segment elevation myocardial infarction (STEMI). METHODS Overall, 2537 consecutive STEMI patients (mean age 56.2 ± 11.7 years, 2111 men, 426 women) undergoing primary angioplasty were enrolled retrospectively into the present study. Patients were categorized according to whether they received RBC transfusions during hospitalization. Clinical characteristics, and in-hospital and long-term outcomes of the primary PCI were analyzed. RESULTS Of the consecutive 2537 patients, 88 (3.4%) received RBC transfusions during the index hospitalization. The transfused patients were older than nontransfused patients (mean age 63.6 ± 12.1 vs. 56.2 ± 11.8, P

Despite the favorable impact of drug eluting stents on stent restenosis, their long-term reliability is considered worrisome by some because of stent thrombosis. Often attributed to adverse reactions to the stent platform, both the drugs and polymer characteristics have been further advanced with current technologies. The present review discussed current drug eluting stents and new developments. (Anadolu Kardiyol Derg 2012; 12: 676-83)