Automatic radiomic feature extraction using deep learning for angiographic parametric imaging of intracranial aneurysms

2019 ◽  
Vol 12 (4) ◽  
pp. 417-421 ◽  
Author(s):  
Alexander R Podgorsak ◽  
Ryan A Rava ◽  
Mohammad Mahdi Shiraz Bhurwani ◽  
Anusha R Chandra ◽  
Jason M Davies ◽  
...  
Keyword(s):  
Operating Characteristic ◽  
Characteristic Curve ◽  
Region Of Interest ◽  
Semantic Segmentation ◽  
Parametric Imaging ◽  
Dice Similarity Coefficient ◽  
Imaging Method ◽  
Digital Subtraction ◽  
Imaging Procedures ◽  
The Mean

BackgroundAngiographic parametric imaging (API) is an imaging method that uses digital subtraction angiography (DSA) to characterize contrast media dynamics throughout the vasculature. This requires manual placement of a region of interest over a lesion (eg, an aneurysm sac) by an operator.ObjectiveThe purpose of our work was to determine if a convolutional neural network (CNN) was able to identify and segment the intracranial aneurysm (IA) sac in a DSA and extract API radiomic features with minimal errors compared with human user results.MethodsThree hundred and fifty angiographic images of IAs were retrospectively collected. The IAs and surrounding vasculature were manually contoured and the masks put to a CNN tasked with semantic segmentation. The CNN segmentations were assessed for accuracy using the Dice similarity coefficient (DSC) and Jaccard index (JI). Area under the receiver operating characteristic curve (AUROC) was computed. API features based on the CNN segmentation were compared with the human user results.ResultsThe mean JI was 0.823 (95% CI 0.783 to 0.863) for the IA and 0.737 (95% CI 0.682 to 0.792) for the vasculature. The mean DSC was 0.903 (95% CI 0.867 to 0.937) for the IA and 0.849 (95% CI 0.811 to 0.887) for the vasculature. The mean AUROC was 0.791 (95% CI 0.740 to 0.817) for the IA and 0.715 (95% CI 0.678 to 0.733) for the vasculature. All five API features measured inside the predicted masks were within 18% of those measured inside manually contoured masks.ConclusionsCNN segmentation of IAs and surrounding vasculature from DSA images is non-inferior to manual contours of aneurysms and can be used in parametric imaging procedures.

scholarly journals Automated Breast Cancer Detection in Digital Mammograms of Various Densities via Deep Learning

2020 ◽  
Vol 10 (4) ◽  
pp. 211 ◽  
Author(s):  
Yong Joon Suh ◽  
Jaewon Jung ◽  
Bum-Joo Cho
Keyword(s):  
Breast Cancer ◽  
Deep Learning ◽  
Operating Characteristic ◽  
Meta Analysis ◽  
Characteristic Curve ◽  
Malignant Lesion ◽  
Model Performance ◽  
Mean Values ◽  
The Mean ◽  
Deep Learning Model

Mammography plays an important role in screening breast cancer among females, and artificial intelligence has enabled the automated detection of diseases on medical images. This study aimed to develop a deep learning model detecting breast cancer in digital mammograms of various densities and to evaluate the model performance compared to previous studies. From 1501 subjects who underwent digital mammography between February 2007 and May 2015, craniocaudal and mediolateral view mammograms were included and concatenated for each breast, ultimately producing 3002 merged images. Two convolutional neural networks were trained to detect any malignant lesion on the merged images. The performances were tested using 301 merged images from 284 subjects and compared to a meta-analysis including 12 previous deep learning studies. The mean area under the receiver-operating characteristic curve (AUC) for detecting breast cancer in each merged mammogram was 0.952 ± 0.005 by DenseNet-169 and 0.954 ± 0.020 by EfficientNet-B5, respectively. The performance for malignancy detection decreased as breast density increased (density A, mean AUC = 0.984 vs. density D, mean AUC = 0.902 by DenseNet-169). When patients’ age was used as a covariate for malignancy detection, the performance showed little change (mean AUC, 0.953 ± 0.005). The mean sensitivity and specificity of the DenseNet-169 (87 and 88%, respectively) surpassed the mean values (81 and 82%, respectively) obtained in a meta-analysis. Deep learning would work efficiently in screening breast cancer in digital mammograms of various densities, which could be maximized in breasts with lower parenchyma density.

The Utility of Pleural Fluid Lactate Dehydrogenase to Adenosine Deaminase Ratio in Pleural Tuberculosis

Respiration ◽  
2020 ◽  
pp. 1-5
Author(s):  
Amanda Beukes ◽  
Jane Alexandra Shaw ◽  
Andreas H. Diacon ◽  
Elvis M. Irusen ◽  
Coenraad F.N. Koegelenberg
Keyword(s):  
Lactate Dehydrogenase ◽  
Adenosine Deaminase ◽  
Pleural Fluid ◽  
Operating Characteristic ◽  
Retrospective Studies ◽  
Characteristic Curve ◽  
Diagnostic Efficiency ◽  
Pleural Tuberculosis ◽  
High Incidence ◽  
The Mean

In high-burden settings, the diagnosis of pleural tuberculosis (TB) is frequently inferred in patients who present with lymphocyte predominant exudative effusions and high adenosine deaminase (ADA) levels. Two recent small retrospective studies suggested that the lactate dehydrogenase (LDH)/ADA ratio is significantly lower in TB than in non-TB pleural effusions and that the LDH/ADA ratio may be useful in differentiating pleural TB from other pleural exudates. We compared the pleural LDH/ADA ratios, ADA levels, and lymphocyte predominance of a prospectively collected cohort of patients with proven pleural TB (<i>n</i> = 160) to those with a definitive alternative diagnosis (<i>n</i> = 68). The mean pleural fluid LDH/ADA ratio was lower in patients with pleural TB than alternative diagnoses (6.2 vs. 34.3, <i>p</i> &#x3c; 0.001). The area under the receiver operating characteristic curve was 0.92 (<i>p</i> &#x3c; 0.001) for LDH/ADA ratio and 0.88 (<i>p</i> &#x3c; 0.001) for an ADA ≥40 U/L alone. A ratio of ≤12.5 had the best overall diagnostic efficiency, while a ratio of ≤10 had a specificity of 90% and a positive predictive value of 95%, with a sensitivity of 78%, making it a clinically useful “rule in” value for pleural TB in high incidence settings. When comparing the LDH/ADA ratio to an ADA level ≥40 U/L in the presence of a lymphocyte predominant effusion, the latter performed better. When lymphocyte values are unavailable, our data suggest that the LDH/ADA ratio is valuable in distinguishing TB effusions from other pleural exudates.

Utility of minimum clinically important difference in assessing pain, disability, and health state after transforaminal lumbar interbody fusion for degenerative lumbar spondylolisthesis

2011 ◽  
Vol 14 (5) ◽  
pp. 598-604 ◽  
Author(s):  
Scott L. Parker ◽  
Owoicho Adogwa ◽  
Alexandra R. Paul ◽  
William N. Anderson ◽  
Oran Aaronson ◽  
...  
Keyword(s):  
Operating Characteristic ◽  
Interbody Fusion ◽  
Characteristic Curve ◽  
Transforaminal Lumbar Interbody Fusion ◽  
Minimum Clinically Important Difference ◽  
Leg Pain ◽  
Sf 36 ◽  
Degenerative Lumbar Spondylolisthesis ◽  
The Mean ◽  
Lumbar Spondylolisthesis

Object Outcome studies for spine surgery rely on patient-reported outcomes (PROs) to assess treatment effects. Commonly used health-related quality-of-life questionnaires include the following scales: back pain and leg pain visual analog scale (BP-VAS and LP-VAS); the Oswestry Disability Index (ODI); and the EuroQol-5D health survey (EQ-5D). A shortcoming of these questionnaires is that their numerical scores lack a direct meaning or clinical significance. Because of this, the concept of the minimum clinically important difference (MCID) has been put forth as a measure for the critical threshold needed to achieve treatment effectiveness. By this measure, treatment effects reaching the MCID threshold value imply clinical significance and justification for implementation into clinical practice. Methods In 45 consecutive patients undergoing transforaminal lumbar interbody fusion (TLIF) for low-grade degenerative lumbar spondylolisthesis-associated back and leg pain, PRO questionnaires measuring BP-VAS, LPVAS, ODI, and EQ-5D were administered preoperatively and at 2 years postoperatively, and 2-year change scores were calculated. Four established anchor-based MCID calculation methods were used to calculate MCID, as follows: 1) average change; 2) minimum detectable change (MDC); 3) change difference; and 4) receiver operating characteristic curve analysis for two separate anchors (the health transition index [HTI] of the 36-Item Short Form Health Survey [SF-36], and the satisfaction index). Results All patients were available at the 2-year follow-up. The 2-year improvements in BP-VAS, LP-VAS, ODI, and EQ-5D scores were 4.3 ± 2.9, 3.8 ± 3.4, 19.5 ± 11.3, and 0.43 ± 0.44, respectively (mean ± SD). The 4 MCID calculation methods generated a range of MCID values for each of the PROs (BP-VAS, 2.1–5.3; LP-VAS, 2.1–4.7; ODI, 11–22.9; and EQ-5D, 0.15–0.54). The mean area under the curve (AUC) for the receiver operating characteristic curve from the 4 PRO-specific calculations was greater for the HTI versus satisfaction anchor (HTI [AUC 0.73] vs satisfaction [AUC 0.69]), suggesting HTI as a more accurate anchor. Conclusions The TLIF-specific MCID is highly variable based on calculation technique. The MDC approach with the SF-36 HTI anchor appears to be most appropriate for calculating MCID because it provided a threshold above the 95% CI of the unimproved cohort (greater than the measurement error), was closest to the mean change score reported by improved and satisfied patients, and was least affected by the choice of anchor. Based on the MDC method with HTI anchor, MCID scores following TLIF are 2.1 points for BP-VAS, 2.8 points for LP-VAS, 14.9 points for ODI, and 0.46 quality-adjusted life years for EQ-5D.

scholarly journals Radiomic Analysis of Contrast-Enhanced Mammography With Different Image Types: Classification of Breast Lesions

2021 ◽  
Vol 11 ◽  
Author(s):  
Simin Wang ◽  
Ning Mao ◽  
Shaofeng Duan ◽  
Qin Li ◽  
Ruimin Li ◽  
...  
Keyword(s):  
Operating Characteristic ◽  
Characteristic Curve ◽  
High Energy ◽  
Breast Lesions ◽  
Wilcoxon Rank Sum Test ◽  
Contrast Enhanced ◽  
Malignant Breast ◽  
The Mean ◽  
Selection Operator

Objective: A limited number of studies have focused on the radiomic analysis of contrast-enhanced mammography (CEM). We aimed to construct several radiomics-based models of CEM for classifying benign and malignant breast lesions.Materials and Methods: The retrospective, double-center study included women who underwent CEM between November 2013 and February 2020. Radiomic analysis was performed using high-energy (HE), low-energy (LE), and dual-energy subtraction (DES) images from CEM. Datasets were randomly divided into the training and testing sets at a ratio of 7:3. The maximum relevance minimum redundancy (mRMR) method and least absolute shrinkage and selection operator (LASSO) logistic regression were used to select the radiomic features and construct the best classification models. The performances of the models were assessed by the area under the receiver operating characteristic curve (AUC) with a 95% confidence interval (CI). Leave-group-out cross-validation (LGOCV) for 100 rounds was performed to obtain the mean AUCs, which were compared by the Wilcoxon rank-sum test and the Kruskal–Wallis rank-sum test.Results: A total of 192 women with 226 breast lesions (101 benign; 125 malignant) were enrolled. The median age was 48 years (range, 22–70 years). For the classification of breast lesions, the AUCs of the best models were 0.931 (95% CI: 0.873–0.989) for HE, 0.897 (95% CI: 0.807–0.981) for LE, 0.882 (95% CI: 0.825–0.987) for DES images and 0.960 (95% CI: 0.910–0.998) for all of the CEM images in the testing set. According to LGOCV, the models constructed with the HE images and all of the CEM images showed the highest mean AUCs for the training (0.931 and 0.938, respectively; P &lt; 0.05 for both) and testing sets (0.892 and 0.889, respectively; P = 0.55 for both), which were significantly higher than those of the two models constructed with the LE and DES images in the training (0.912 and 0.899, respectively; all P &lt; 0.05) and testing sets (0.866 and 0.862, respectively; all P &lt; 0.05).Conclusions: Radiomic analysis of CEM images was valuable for classifying benign and malignant breast lesions. The use of HE images or all three types of CEM images can achieve the best performance.

scholarly journals A Simple and Novel Noninvasive Method of Estimating Markedly Elevated Pulmonary Vascular Resistance in Patients with Pre-capillary Pulmonary Hypertension

2021 ◽  
Author(s):  
Ya-Nan Zhai ◽  
Ai-Li Li ◽  
Xin-Cao Tao ◽  
Wan-Mu Xie ◽  
Qian Gao ◽  
...  
Keyword(s):  
Pulmonary Hypertension ◽  
Pulmonary Vascular Resistance ◽  
Vascular Resistance ◽  
Operating Characteristic ◽  
Characteristic Curve ◽  
Curve Analysis ◽  
Internal Diameter ◽  
Noninvasive Method ◽  
Simple Method ◽  
The Mean

Abstract Background: Several echocardiographic methods to estimate pulmonary vascular resistance (PVR) in patients with pulmonary hypertension (PH) have been proposed. So far, most studies have focused on relatively low PVR. We aimed to clarify the clinical usefulness of our new echocardiographic index of evaluating markedly elevated PVR in pre-capillary PH patients. Methods: We studied 129 consecutive patients with pre-capillary PH. We estimated the mean pulmonary artery pressure using echocardiography (mPAPEcho) and measured LV internal diameter at end diastole (LVIDd). The ratio of mPAPEcho / LVIDd was then correlated with invasive PVR. Using receiver operating characteristic curve analysis, a cutoff value for the index was generated to identify patients with PVR > 15 Wood units (WU). Results: mPAPEcho / LVIDd correlated well with PVR (r = 0.70, P < 0.0001). There was a better correlation between PVR and mPAPEcho / LVIDd in patients with PVR > 15 WU compared with TRV2 /TVIRVOT and sPAPEcho / LVIDd. A cut-off value of 1.14 had an 80.0% sensitivity and 74.7% specificity to determine PVR > 15 WU (AUC=0.840, p<0.0001). Conclusions: The index of mPAPEcho / LVIDd could be a valuable noninvasive and simple method of estimating markedly elevated PVR in pre-capillary PH patients.

Patient-Doctor Contact Interval and Clinical Outcomes in Continuous Ambulatory Peritoneal Dialysis Patients

2017 ◽  
Vol 45 (4) ◽  
pp. 346-352 ◽  
Author(s):  
Chunyan Yi ◽  
Qunying Guo ◽  
Jianxiong Lin ◽  
Jianying Li ◽  
Xueqing Yu ◽  
...  
Keyword(s):  
Peritoneal Dialysis ◽  
Clinical Outcomes ◽  
Operating Characteristic ◽  
Patient Survival ◽  
Characteristic Curve ◽  
Survival Rates ◽  
Guangzhou City ◽  
Clinical Events ◽  
The Mean

Background: The optimal patient-doctor contact (PDC) interval remains unknown in peritoneal dialysis (PD) patients. The aim was to investigate the association between PDC interval and clinical outcomes in continuous ambulatory PD (CAPD) patients. Methods: In this retrospective cohort study, CAPD patients who resided in Guangzhou city between January 2006 and December 2012 were included. According to receiver operating characteristic curve analysis, all patients were classified as high (PDC interval ≤2 months) and low (PDC interval >2 months) PDC frequency groups. Biochemical data, clinical events, and clinical outcomes during the follow-up period were compared. Results: Of 433 CAPD patients, the mean age was 51.3 ± 15.7 years, 54.3% of patients were male, and 29.1% with diabetes. The median vintage of PD was 45.8 (26.3-69.1) months. Patients with high PDC frequency (n = 233) had better patient-survival rates (99.6, 87.7, and 76.5% vs. 92.7, 76.5, and 58.7% at 1, 3, and 5 years; p < 0.001), lower peritonitis rate (0.17 vs. 0.23 episodes per patient-year; p < 0.001), and hospitalization rate (0.49 vs. 0.67 episodes per patient-year; p < 0.001) than those in the low PDC frequency group (n = 200). After adjustment for confounders, PDC interval of no more than 2 months was independently associated with better patient survival (hazard ratio 0.60, 95% CI 0.42-0.86, p = 0.006). Conclusion: A PDC interval of 2 months or less was associated with better clinical outcomes in CAPD patients. This indicates that a shorter PDC interval should be encouraged for them to achieve better clinical outcomes.

scholarly journals Efficacy of Quantitative Muscle Ultrasound Using Texture-Feature Parametric Imaging in Detecting Pompe Disease in Children

Entropy ◽  
2019 ◽  
Vol 21 (7) ◽  
pp. 714
Author(s):  
Hong-Jen Chiou ◽  
Chih-Kuang Yeh ◽  
Hsuen-En Hwang ◽  
Yin-Yin Liao
Keyword(s):  
Pompe Disease ◽  
Late Onset ◽  
Characteristic Curve ◽  
Texture Feature ◽  
Rectus Femoris ◽  
Parametric Imaging ◽  
Imaging Method ◽  
Healthy Children ◽  
Linear Discriminant ◽  
Optimal Feature

Pompe disease is a hereditary neuromuscular disorder attributed to acid α-glucosidase deficiency, and accurately identifying this disease is essential. Our aim was to discriminate normal muscles from neuropathic muscles in children affected by Pompe disease using a texture-feature parametric imaging method that simultaneously considers microstructure and macrostructure. The study included 22 children aged 0.02–54 months with Pompe disease and six healthy children aged 2–12 months with normal muscles. For each subject, transverse ultrasound images of the bilateral rectus femoris and sartorius muscles were obtained. Gray-level co-occurrence matrix-based Haralick’s features were used for constructing parametric images and identifying neuropathic muscles: autocorrelation (AUT), contrast, energy (ENE), entropy (ENT), maximum probability (MAXP), variance (VAR), and cluster prominence (CPR). Stepwise regression was used in feature selection. The Fisher linear discriminant analysis was used for combination of the selected features to distinguish between normal and pathological muscles. The VAR and CPR were the optimal feature set for classifying normal and pathological rectus femoris muscles, whereas the ENE, VAR, and CPR were the optimal feature set for distinguishing between normal and pathological sartorius muscles. The two feature sets were combined to discriminate between children with and without neuropathic muscles affected by Pompe disease, achieving an accuracy of 94.6%, a specificity of 100%, a sensitivity of 93.2%, and an area under the receiver operating characteristic curve of 0.98 ± 0.02. The CPR for the rectus femoris muscles and the AUT, ENT, MAXP, and VAR for the sartorius muscles exhibited statistically significant differences in distinguishing between the infantile-onset Pompe disease and late-onset Pompe disease groups (p < 0.05). Texture-feature parametric imaging can be used to quantify and map tissue structures in skeletal muscles and distinguish between pathological and normal muscles in children or newborns.

Protein Carbonyl, But Not Malondialdehyde, Is Associated With ICU Mortality in Patients With Septic Shock

2017 ◽  
Vol 34 (8) ◽  
pp. 669-673 ◽  
Author(s):  
Nara Aline Costa ◽  
Ana Lucia Gut ◽  
Paula Schmidt Azevedo ◽  
Ana Angelica Henrique Fernandes ◽  
Bertha Furlan Polegato ◽  
...  
Keyword(s):  
Septic Shock ◽  
Operating Characteristic ◽  
Characteristic Curve ◽  
Area Under The Curve ◽  
Protein Carbonyl ◽  
Apache Ii ◽  
Apache Ii Score ◽  
Icu Mortality ◽  
Logistic Regression Models ◽  
The Mean

Background:The objective of our study was to evaluate the association of serum malondialdehyde (MDA) and protein carbonyl concentration with intensive care unit (ICU) mortality in patients with septic shock.Methods:We prospectively evaluated 175 patients aged over 18 years with septic shock upon ICU admission. However, 16 patients were excluded. Thus, 159 patients were enrolled in the study. In addition, we evaluated 16 control patients. At the time of the patients’ enrollment, demographic information was recorded. Blood samples were taken within the first 24 hours of the patient’s admission to determine serum MDA and protein carbonyl concentrations.Results:The mean age was 67.3 ± 15.9 years, 44% were males, and the ICU mortality rate was 67.9%. Median MDA concentration was 1.53 (0.83-2.22) µmol/L, and median protein carbonyl concentration was 24.0 (12.7-32.8) nmol/mL. Patients who died during ICU stay had higher protein carbonyl concentration. However, there was no difference in MDA levels between these patients. Receiver operating characteristic curve analysis showed that higher levels of protein carbonyl were associated with ICU mortality (area under the curve: 0.955; 95% confidence interval [CI]: 0.918-0.992; P < .001) at the cutoff of >22.83 nmol/mL (sensibility: 80.4% and specificity: 98.1%). In the logistic regression models, protein carbonyl concentrations (odds ratio [OR]: 1.424; 95% CI: 1.268-1.600; P < .001), but not MDA concentrations (OR: 1.087; 95% CI: 0.805-1.467; P = .59), were associated with ICU mortality when adjusted for age, gender, and Acute Physiology and Chronic Health Evaluation (APACHE) II score; and when adjusted by APACHE II score, lactate, and urea; protein carbonyl concentrations (OR: 1.394; 95% CI: 1.242-1.564; P < .001); and MDA (OR: 1.054; 95% CI: 0.776-1.432; P = .73).Conclusion:In conclusion, protein carbonyl, but not MDA, concentration is associated with ICU mortality in patients with septic shock.

scholarly journals Utility of arterial spin labeling perfusion magnetic resonance imaging in prediction of angiographic vascularity of meningiomas

2016 ◽  
Vol 125 (3) ◽  
pp. 536-543 ◽  
Author(s):  
Roh-Eul Yoo ◽  
Tae Jin Yun ◽  
Young Dae Cho ◽  
Jung Hyo Rhim ◽  
Koung Mi Kang ◽  
...  
Keyword(s):  
Digital Subtraction Angiography ◽  
Arterial Spin Labeling ◽  
Characteristic Curve ◽  
Tissue Perfusion ◽  
Spin Labeling ◽  
Perfusion Magnetic Resonance Imaging ◽  
Digital Subtraction ◽  
Grading Scale ◽  
The Mean ◽  
Contrast Media Administration

OBJECTIVE Arterial spin labeling perfusion-weighted imaging (ASL-PWI) enables quantification of tissue perfusion without contrast media administration. The aim of this study was to explore whether cerebral blood flow (CBF) from ASL-PWI can reliably predict angiographic vascularity of meningiomas. METHODS Twenty-seven patients with intracranial meningiomas, who had undergone preoperative ASL-PWI and digital subtraction angiography prior to resection, were included. Angiographic vascularity was assessed using a 4-point grading scale and meningiomas were classified into 2 groups: low vascularity (Grades 0 and 1; n = 11) and high vascularity (Grades 2 and 3; n = 16). Absolute CBF, measured at the largest section of the tumor, was normalized to the contralateral gray matter. Correlation between the mean normalized CBF (nCBF) and angiographic vascularity was determined and the mean nCBF values of the 2 groups were compared. Diagnostic performance of the nCBF for differentiating between the 2 groups was assessed. RESULTS The nCBF had a significant positive correlation with angiographic vascularity (ρ = 0.718; p < 0.001). The high-vascularity group had a significantly higher nCBF than the low-vascularity group (3.334 ± 2.768 and 0.909 ± 0.468, respectively; p = 0.003). At the optimal nCBF cutoff value of 1.733, sensitivity and specificity for the differential diagnosis of the 2 groups were 69% (95% CI 41%–89%) and 100% (95% CI 72%–100%), respectively. The area under the receiver operating characteristic curve was 0.875 (p < 0.001). CONCLUSIONS ASL-PWI may provide a reliable and noninvasive means of predicting angiographic vascularity of meningiomas. It may thus assist in selecting potential candidates for preoperative digital subtraction angiography and embolization in clinical practice.

scholarly journals Use of Procalcitonin in Patients on Chronic Hemodialysis: Procalcitonin Is Not Related with Increased Serum Calcitonin

ISRN Urology ◽  
2012 ◽  
Vol 2012 ◽  
pp. 1-6 ◽  
Author(s):  
Ken-Ichi Mori ◽  
Mitsuru Noguchi ◽  
Yasuhiro Sumino ◽  
Fuminori Sato ◽  
Hiromitsu Mimata
Keyword(s):  
Bacterial Infections ◽  
Operating Characteristic ◽  
Characteristic Curve ◽  
Chronic Hemodialysis ◽  
Infection Group ◽  
Serum Calcitonin ◽  
Reactive Protein ◽  
The Mean ◽  
Wbc Count ◽  
Group Serum

Objectives. To investigate whether procalcitonin (PCT) could be useful for detecting bacterial infections in patients on hemodialysis (HD) and with increased calcitonin (CT). Methods. This prospective study included 42 males and 34 females on HD. The infection group consisted of 15 patients with proven bacterial infections; the other 61 patients were designated as the noninfection group. Serum C-reactive protein (CRP), interleukin (IL)-6, white blood cell (WBC) count, immature and total neutrophil (I/T) ratio, and CT were measured at the beginning of HD, and serum PCT levels at the beginning of HD and after HD. Results. The mean CT level in the both groups was apparently higher than that of nonchronic kidney disease. Significantly higher values between the infection and noninfection groups were seen for CRP, IL-6, WBC, I/T ratio, PCT, and CT. The PCT value of the area under the receiver operating characteristic curve was 0.921, which was significantly higher than the values for CRP (0.853; ), IL-6 (0.739; ), WBC (0.692; ), and I/T ratio (0.584; ). Conclusions. PCT was useful marker of bacterial infection in patients on HD and with increased CT. PCT levels should be determined before HD.

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