Highest Area Under The Receiver Operating Characteristic Curve Value Research Articles

Use of MRI Radiomics Models in Evaluating the Low HER2 Expression in Breast Cancer.

To investigate the magnetic resonance imaging (MRI) radiomics models in evaluating the human epidermal growth factor receptor 2(HER2) expression in breast cancer. <P> Materials and Methods: The MRI data of 161 patients with invasive ductal carcinoma (non-special type) of breast cancer were retrospectively collected, and the MRI radiomics models were established based on the MRI imaging features of the fat suppression T2 weighted image (T2WI) sequence, dynamic contrast-enhanced (DCE)-T1WIsequence and joint sequences. The T-test and the least absolute shrinkage and selection operator (LASSO) algorithm were used for feature dimensionality reduction and screening, respectively, and the random forest (RF) algorithm was used to construct the classification model. <P> Results: The model established by the LASSO-RF algorithm was used in the ROC curve analysis. In predicting the low expression state of HER2 in breast cancer, the radiomics models of the fat suppression T2WI sequence, DCE-T1WI sequence, and the combination of the two sequences showed better predictive efficiency. In the receiver operating characteristic (ROC) curve analysis for the verification set of low, negative, and positive HER2 expression, the area under the ROC curve (AUC) value was 0.81, 0.72, and 0.62 for the DCE-T1WI sequence model, 0.79, 0.65 and 0.77 for the T2WI sequence model, and 0.84, 0.73 and 0.66 for the joint sequence model, respectively. The joint sequence model had the highest AUC value. <P> Conclusions: The MRI radiomics models can be used to effectively predict the HER2 expression in breast cancer and provide a non-invasive and early assistant method for clinicians to formulate individualized and accurate treatment plans.

Detection of recurrence sites using 18F-fluorocholine PET/CT in prostate cancer patients with PSA failure.

The optimal condition for the clinical application of 18F-fluorocholine positron emission tomography-computed tomography (FCH-PET/CT) to detect recurrence sites in prostate-specific antigen (PSA) failure remains unclear due to the heterogeneity of prostate cancer failure. We aimed to evaluate the detection rate of FCH-PET/CT in prostate cancer patients with PSA failure and to determine the optimal PSA level for performing FCH-PET/CT. FCH-PET/CT was conducted in 89 patients diagnosed with PSA failure after radical treatment (radical prostatectomy in 75 and definitive radiotherapy in 14) between November 2018 and May 2021. Detection rates were examined via receiver operating characteristic (ROC) analysis, and multivariable logistic regression was performed to identify factors affecting positive FCH-PET/CT findings. We also conducted subgroup analyses according to the PSA failure patterns after the radical treatment (persistently high PSA [N=48] and biochemical recurrence [BCR] [N=41]). FCH-PET/CT demonstrated a 59.6% overall detection rate, and the optimal PSA threshold for detecting positive findings was ≥ 1.00ng/mL at the time of imaging. On multivariable analysis, PSA > 1.00ng/mL (P<0.001) was a significant predictor of positive FCH-PET/CT findings, especially regarding distant bone metastases (P<0.001) and recurrence outside the pelvis (P<0.001). In a subgroup analysis of patients with BCR after initial radical treatment, the area under the ROC curve (AUC) was 0.82, and PSA ≥ 1.75ng/mL was the optimal value for identifying positive FCH-PET/CT findings. This PSA value was also associated with significantly higher detection rates of distant bone metastases and outside-pelvis metastasis (P<0.001, both). FCH-PET/CT is a clinically useful tool for detecting tumor recurrence sites in prostate cancer patients with PSA failure if PSA has exceeded a certain value at the time of imaging. Particularly, higher AUC values were observed when FCH-PET/CT was performed in patients with BCR after initial treatment.

Amide Proton Transfer-weighted MRI combined with serum prostate-specific antigen levels for differentiating malignant prostate lesions from benign prostate lesions: a retrospective cohort study

BackgroundEarly diagnosis of prostate cancer improves its prognosis, while it is essential to upgrade screening tools. This study aimed to explore the value of a novel functional magnetic resonance imaging (MRI) technique, namely amide proton transfer (APT)-weighted MRI, combined with serum prostate-specific antigen (PSA) levels to differentiate malignant prostate lesions from benign prostate lesions.MethodsData of patients who underwent prostate examinations at Chongqing University Cancer Hospital between July 2019 and March 2022 were retrospectively analyzed. All patients underwent T2-weighted imaging (T2WI), APT, diffusion-weighted imaging (DWI), and dynamic contrast-enhanced (DCE) MRI. Two radiologists analyzed the images independently. The ability of the quantitative parameters alone or in different combinations in differentiating malignant prostate lesions from benign prostate lesions were compared by using receiver operating characteristic (ROC) curves. According to the DeLong test, the combined parameters were significantly different from the corresponding single parameter (P < 0.05).ResultsA total of 79 patients were finally enrolled, including 52 patients in the malignant group and 27 patients in the benign group. The separate assessment of indexes revealed that APTmax, APTmean, mean apparent diffusion coefficient (ADCmean), ADCmax, ADCmin, tPAD, free prostate-specific antigen (FPSA), FPSA/total prostate-specific antigen (tPSA), and PSA density (PSAD) were significantly different between the two groups (P < 0.05), while APTmin was not significantly different between the two groups (P > 0.05). APTmax and APTmean had the high values of area under the ROC curve (AUC), which were 0.780 and 0.710, respectively. APTmax had a high sensitivity, and APTmean had a high specificity. The combination of APTmax, APTmean, ADCmean, and PSAD had the highest AUC value (AUC: 0.880, sensitivity: 86.540, specificity: 78.260).ConclusionAPTmax, APTmean, ADCmean, ADCmin, tPAD, FPSA, and PSAD showed to have a high value in differentiating malignant prostate lesions from benign prostate lesions in the separate assessment of indexes. The combination of APTmax, APTmean, ADCmean, and PSAD had the highest diagnostic value.

Early prediction of pathological complete response to neoadjuvant chemotherapy combining DCE-MRI and apparent diffusion coefficient values in breast Cancer

IntroductionImproving the early prediction of neoadjuvant chemotherapy (NAC) efficacy in breast cancer can lead to an improved prediction of the final prognosis of patients, which would be useful for promoting individualized treatment. This study aimed to explore the value of the combination of dynamic contrast-enhanced (DCE)-MRI parameters and apparent diffusion coefficient (ADC) values in the early prediction of pathological complete response (pCR) to NAC for breast cancer.MethodsA total of 119 (range, 28−69 years) patients with biopsy-proven breast cancer who received two cycles of NAC before breast surgery were retrospectively enrolled from our hospital database. Patients were divided into pCR and non pCR groups according to their pathological responses; a total of 24 patients achieved pCR, while 95 did not. The quantitative (Ktrans; Kep; Ve; IAUC) and semiquantitative parameters (W-in; W-out; TTP) of DCE-MRI that were significantly different between groups were combined with ADC values to explore their value in the early prediction of pCR to NAC for breast cancer. The independent T test was performed to compare the differences in DCE-MRI parameters and ADC values between the two groups. Receiver operating characteristic (ROC) curves were plotted, and the area under the ROC curve (AUC), sensitivity and specificity were calculated to evaluate the performance of the prediction.ResultsThe Ktrans, Kep, IAUC, ADC, W-in and TTP values were significantly different between the pCR and non pCR groups after NAC. The AUC (0.845) and specificity (95.79%) of the combined Ktrans, Kep, IAUC and ADC values were both higher than those of the individual parameters. The combination of W-in, TTP and ADC values had the highest AUC value (0.886) in predicting pCR, with a sensitivity and specificity of 87.5% and 82.11%, respectively.ConclusionsThe results suggested that the combination of ADC values and quantitative and semiquantitative DCE-MRI parameters, especially the combination of W-in, TTP, and ADC values, may improve the early prediction of pCR in breast cancer.

Combining Structural and Vascular Parameters to Discriminate Among Glaucoma Patients, Glaucoma Suspects, and Healthy Subjects.

PurposeCompare the ability of peripapillary and macular structural parameters, vascular parameters, and their integration to discriminate among glaucoma, suspected glaucoma (GS), and healthy controls (HCs).MethodsIn this study, 196 eyes of 119 patients with glaucoma (n = 81), patients with GS (n = 48), and HCs (n = 67) underwent optical coherence tomography (OCT) and OCT angiography to measure peripapillary retinal nerve fiber layer (pRNFL), macular ganglion cell–inner plexiform layer (mGCIPL) thicknesses, radial peripapillary capillary perfusion density (RPC-PD), and macular GCIPL perfusion density (GCIPL-PD). Parameters were integrated regionally with logistic regression and globally with machine learning algorithms. Diagnostic performances were evaluated with area under the receiver operating characteristic (AUROC) curves.ResultsPatients with glaucoma had mild to moderate damage (median, −3.3 dB; interquartile range, −6.5 to −1.4). In discriminating between patients with glaucoma and the HCs, pRNFL thickness had higher AUROC curve values than RPC-PD for average (0.87 vs. 0.62; P < 0.001), superior (0.86 vs. 0.54; P < 0.001), inferior (0.90 vs. 0.71; P < 0.001), and temporal (0.65 vs. 0.51; P = 0.02) quadrants. mGCIPL thickness had higher AUROC curve values than GCIPL-PD for average (0.84 vs. 0.68; P < 0.001), superotemporal (0.76 vs. 0.65; P = 0.016), superior (0.72 vs. 0.57; P = 0.004), superonasal (0.70 vs. 0.56; P = 0.01), inferotemporal (0.90 vs. 0.72; P < 0.001), inferior (0.87 vs. 0.69; P < 0.001), and inferonasal (0.78 vs. 0.65, P = 0.012) sectors. All structural multisector indices had higher diagnostic ability than vascular ones (P < 0.001). Combined structural–vascular indices did not outperform structural indices. Similar results were found to discriminate glaucoma from GS.ConclusionsCombining structural and vascular parameters in a structural–vascular index does not improve diagnostic ability over structural parameters alone.Translational RelevanceOCT angiography does not add additional benefit to structural OCT in early to moderate glaucoma diagnosis.

Performance of Two Novel Obesity Indicators for the Management of Metabolic Syndrome in Young Adults.

BackgroundMetabolic syndrome (MetS) is a pathophysiological change based on the abnormal metabolism of many substances. The study aims to investigate the performance of visceral adiposity index (VAI) and lipid accumulation product (LAP) of MetS in young adults.Methods448 young adults aged between 19 and 24 years old in Qinhuangdao had been included in this cross-sectional study. Receiver operating characteristic (ROC) curve analyses were used to assess the accuracy of these two obesity indicators for MetS.ResultsThe prevalence of MetS was 2.0%. In male subjects, LAP had the highest area under the ROC curve (AUC) value (AUC = 0.963), followed by VAI (AUC = 0.937). In female subjects, LAP also had the highest AUC value (AUC = 0.931), followed by VAI (AUC = 0.861). No significant difference was found between the two obesity indicators (P > 0.05).ConclusionThe two obesity indicators were valuable for the screening of MetS in young adults, and LAP was the simpler of the two.

Characteristics of the wideband absorbance of acoustic energy in children (3–7 years old) with otitis media with effusion

ObjectiveThis study aimed to investigate the characteristics of the wideband absorbance (WBA) of acoustic energy in children (3–7 years old) with otitis media with effusion (OME) under environmental ear-canal air pressure and tympanometric peak pressure and to determine the diagnostic value of the acoustic energy absorption rate (AR) in OME at different frequencies. MethodsA total of 178 children aged 3–7 years were enrolled in the study between April and October 2018. They were separated into two groups: those with middle ear effusion were placed in the OME group (n = 80; 136 ears), while those without OME (n = 98; 182 ears) were placed in the control group. A WBA test was performed on the children in both groups under environmental ear-canal pressure and tympanometric peak pressure to analyze the changing characteristics of the AR value within the 0.226–8 kHz range. ResultsUnder ambient ear-canal air pressure, the AR of the OME group in each frequency band was significantly lower than that of the control group (P < 0.01). Under tympanometric peak pressure, the AR of the OME group in most frequencies was also significantly lower than those of the control group (P < 0.01) except in the 2–2.5 kHz range. The area under the receiver operating characteristic curve (AUROC) was highest at 0.47–1.03 kHz: 0.96 and 0.94 at ambient ear-canal pressure and tympanometric peak pressure, respectively. Of the single frequency points, those at 0.65, 0.67, 0.69, 0.71, and 0.73 kHz had a higher AUROC value (0.96–0.97) under both ambient ear-canal air pressure and tympanometric peak pressure. The difference in the AUROC values of the two pressure conditions was not statistically significant (P < 0.01). ConclusionOverall, WBA is an effective method of diagnosing OME in children. The frequency band with the most predictive value of AR for OME is 0.47–1.03 kHz. Middle ear effusion can be quickly identified by observing AR values in this frequency range, which provides a diagnostic basis for OME.

Application of machine learning approaches for osteoporosis risk prediction in postmenopausal women.

Osteoporosis is a silent disease until it results in fragility fractures. However, early diagnosis of osteoporosis provides an opportunity to detect and prevent fractures. We aimed to develop machine learning approaches to achieve high predictive ability for osteoporosis risk that could help primary care providers identify which women are at increased risk of osteoporosis and should therefore undergo further testing with bone densitometry. We included all postmenopausal Korean women from the Korea National Health and Nutrition Examination Surveys (KNHANES V-1, V-2) conducted in 2010 and 2011. Machine learning models using methods such as the k-nearest neighbors (KNN), decision tree (DT), random forest (RF), gradient boosting machine (GBM), support vector machine (SVM), artificial neural networks (ANN), and logistic regression (LR) were developed to predict osteoporosis risk. We analyzed the effect of applying the machine learning algorithms to the raw data and featuring the selected data only where the statistically significant variables were included as model inputs. The accuracy, sensitivity, specificity, and area under the receiver operating characteristic curve (AUROC) were used to evaluate performance among the seven models. A total of 1792 patients were included in this study, of which 613 had osteoporosis. The raw data consisted of 19 variables and achieved performances (in terms of AUROCs) of 0.712, 0.684, 0.727, 0.652, 0.724, 0.741, and 0.726 for KNN, DT, RF, GBM, SVM, ANN, and LR with fivefold cross-validation, respectively. The feature selected data consisted of nine variables and achieved performances (in terms of AUROCs) of 0.713, 0.685, 0.734, 0.728, 0.728, 0.743, and 0.727 for KNN, DT, RF, GBM, SVM, ANN, and LR with fivefold cross-validation, respectively. In this study, we developed and compared seven machine learning models to accurately predict osteoporosis risk. The ANN model performed best when compared to the other models, having the highest AUROC value. Applying the ANN model in the clinical environment could help primary care providers stratify osteoporosis patients and improve the prevention, detection, and early treatment of osteoporosis.

Importance of lipid ratios for predicting intracranial atherosclerotic stenosis.

BackgroundThis study aims to investigate the association of lipid ratios with intracranial atherosclerotic stenosis (ICAS) in a Chinese population.MethodsThis cross-sectional study included 658 consecutive patients with ischemic stroke. Intracranial and extracranial arteries were evaluated for atherosclerotic stenosis using digital subtraction angiography or computed tomography angiography. Lipid ratios [total cholesterol (TC)/high-density lipoprotein-cholesterol (HDL-C), triglycerides (TG)/HDL-C, low-density lipoprotein-cholesterol (LDL-C)/HDL-C, non-high-density lipoprotein-cholesterol (non-HDL-C)/HDL-C, remnant cholesterol (RC)/HDL-C, apolipoprotein B (apo B)/apolipoprotein A-I (apo A-I), and apo B/HDL-C] were calculated.ResultsThe TC/HDL-C, LDL-C/HDL-C, RC/HDL-C, non-HDL-C/HDL-C, apo B/HDL-C and apo B/apo A-I ratios (all P < 0.05) were significantly associated with ICAS but not with extracranial atherosclerotic stenosis after adjustment for confounding factors. Receiver operating characteristic (ROC) curves analysis revealed that the apo B/apo A-I ratio had the largest area under the ROC curve (AUC) among lipid levels alone and for lipid ratios (AUC = 0.588). Lipid ratios had higher AUC values than those for lipid levels alone for the identification of ICAS.ConclusionThe TC/HDL-C, LDL-C/HDL-C, RC/HDL-C, non-HDL-C/HDL-C apo B/HDL-C, and apo B/apo A-I ratios were significantly related to ICAS risk. Compared with the other variables tested, the apo B/apo A-I ratio appeared to be a better discriminator for identifying ICAS risk in stroke patients.

Comparison of Injury Severity Score, Glasgow Coma Scale, and Revised Trauma Score in Predicting the Mortality and Prolonged ICU Stay of Traumatic Young Children: A Cross-Sectional Retrospective Study.

Introduction The purpose of this study was to examine the capacity of commonly used trauma scoring systems such as the Glasgow Coma Scale (GCS), Injury Severity Score (ISS), and Revised Trauma Score (RTS) to predict outcomes in young children with traumatic injuries. Methods This retrospective study was conducted for the period from 2009 to 2016 in Kaohsiung Chang Gung Memorial Medical Hospital, a level I trauma center. We included all children under the age of 6 years admitted to the hospital via the emergency department with any traumatic injury and compared the trauma scores of GCS, ISS, and RTS on patients' outcome. The primary outcomes were mortality and prolonged Intensive Care Unit (ICU) stay, with the latter defined as an ICU stay longer than 14 days. The secondary outcome was the hospital length of stay (HLOS). Receiver operating characteristic (ROC) analysis was also adopted with the value of the area under the ROC curve (AUC) for comparing trauma score prediction with patient mortality. Cutoff values from each trauma score for mortality prediction were also measured by determining the point along the ROC curve where Youden's index was maximum. Results We included a total of 938 patients in this study, with a mean age of 3.1 ± 1.82 years. The mortality rate was 0.9%, and 93 (9.9%) patients had a prolonged ICU stay. An elevated ISS (34 ± 19.9 vs. 5 ± 5.1, p=0.004), lower GCS (8 ± 5.0 vs. 15 ± 1.3, p=0.006), and lower RTS (5.58 ± 1.498 vs. 7.64 ± 0.640, p=0.006) were all associated with mortality. All three scores were considered to be independent risk factors of mortality and prolonged ICU stay and had a linear correlation with increased HLOS. With regard to predicting mortality, ISS has the highest AUC value (ISS: 0.975; GCS: 0.864; and RTS: 0.899). The prediction cutoff values of ISS, GCS, and RTS on mortality were 15, 11, and 7, respectively. Conclusion Regarding traumatic injuries in young children, worse ISS, GCS, and RTS were all associated with increased mortality, prolonged ICU stay, and longer hospital LOS. Of these scoring systems, ISS was the best at predicting mortality.

Mir-421 in plasma as a potential diagnostic biomarker for precancerous gastric lesions and early gastric cancer.

ObjectiveMicroRNA (miR)-421 plays a key role in cancer progression. It has been reported that circulating miR-421may be a potential tumor marker for the diagnosis of several cancers. However, the role of miR-421 in plasma as a potential biomarker in the diagnosis of precancerous gastric lesions (Pre) and early-stage gastric cancer (GC) remains poorly understood. In this study, we investigated miR-421 in plasma as a novel potential biomarker for the detection of precancerous gastric lesions and early-stage (GC).Materials & MethodsThe miRNA content was determined by quantitative real-time polymerase chain reaction (qRT-PCR). MiR-421 content in all subjects was normalized by endogenous miRNA (miR-16). The diagnostic value of miR-421 for Pre and GC was assessed by comparing receiver operating characteristic (ROC) analysis with traditional tumor markers, including CEA, CA125, CA153, CA211 and CA50. The correlation between the expression of miR-421 and the pathological characteristics of Pre and GC was analyzed.ResultsElevated expression of miR-421 in plasma can robustly distinguish the normal population from Pre and GC cases, especially in the early stages of gastric cancer cases (all p < 0.05). The ROC analyses showed that the area under the ROC curve (AUC), sensitivity, accuracy and Youden index of miR-421 were superior to traditional tumor markers (CEA, CA125, CA153, CA211, and CA50) in GC diagnosis, while its specificity was higher than CEA, CA153 and CA50 (all p < 0.05). MiR-421 in plasma had higher AUC value than AFP, CA153, CA211 and CA50 in the diagnosis of Pre (all p < 0.05), while specificity, accuracy and Youden index of miR-421 was only lower than CA211. The efficiency of miR-421 in the diagnosis of GC was significantly higher than that of CA211 and CA50, and it was significantly higher than CA153, CA211 and CA50 in the diagnosis of Pre (all p < 0.05). In addition, up-regulation of miR-421 occurred initially in precancerous gastric lesions as well as in the early stage of GC. ConclusionsOverexpression of plasma miR-421 is a novel biomarker for the detection of precancerous lesions and early gastric cancer.

Landslide Susceptibility Mapping Based on Weighted Gradient Boosting Decision Tree in Wanzhou Section of the Three Gorges Reservoir Area (China)

The main goal of this study is to produce a landslide susceptibility map in the Wanzhou section of the Three Gorges reservoir area (China) with a weighted gradient boosting decision tree (weighted GBDT) model. According to the current research on landslide susceptibility mapping (LSM), the GBDT method is rarely used in LSM. Furthermore, previous studies have rarely considered the imbalance of landslide samples and simply regarded the LSM problem as a binary classification problem. In this paper, we considered LSM as an imbalanced learning problem and obtained a better predictive model using the weighted GBDT method. The innovations of the article mainly include the following two points: introducing the GBDT model into the evaluation of landslide susceptibility; using the weighted GBDT method to deal with the problem of landslide sample imbalance. The logistic regression (LR) model and gradient boosting decision tree (GBDT) model were also used in the study to compare with the weighted GBDT model. Five kinds of data from different data source were used in the study: geology, topography, hydrology, land cover, and triggered factors (rainfall, earthquake, land use, etc.). Twenty nine environmental parameters and 233 landslides were used as input data. The receiver operating characteristic (ROC) curve, the area under the ROC curve (AUC) value, and the recall value were used to estimate the quality of the weighted GBDT model, the GBDT model, and the LR model. The results showed that the GBDT model and the weighted GBDT model had a higher AUC value (0.977, 0.976) than the LR model (0.845); the weighted GBDT model had a little higher AUC value (0.977) than the GBDT model (0.976); and the weighted GBDT model had a higher recall value (0.823) than the GBDT model (0.426) and the LR model (0.004). The weighted GBDT method could be considered to have the best performance considering the AUC value and the recall value in landslide susceptibility mapping dealing with imbalanced landslide data.

Task-based evaluation of a 4D MAP-RBI-EM image reconstruction method for gated myocardial perfusion SPECT using a human observer study

We evaluated the performance of a new 4D image reconstruction method for improved 4D gated myocardial perfusion (MP) SPECT using a task-based human observer study. We used a realistic 4D NURBS-based Cardiac-Torso (NCAT) phantom that models cardiac beating motion. Half of the population was normal; the other half had a regional hypokinetic wall motion abnormality. Noise-free and noisy projection data with 16 gates/cardiac cycle were generated using an analytical projector that included the effects of attenuation, collimator-detector response, and scatter (ADS), and were reconstructed using the 3D FBP without and 3D OS-EM with ADS corrections followed by different cut-off frequencies of a 4D linear post-filter. A 4D iterative maximum a posteriori rescaled-block (MAP-RBI)-EM image reconstruction method with ADS corrections was also used to reconstruct the projection data using various values of the weighting factor for its prior. The trade-offs between bias and noise were represented by the normalized mean squared error (NMSE) and averaged normalized standard deviation (NSDav), respectively. They were used to select reasonable ranges of the reconstructed images for use in a human observer study. The observers were trained with the simulated cine images and were instructed to rate their confidence on the absence or presence of a motion defect on a continuous scale. We then applied receiver operating characteristic (ROC) analysis and used the area under the ROC curve (AUC) index. The results showed that significant differences in detection performance among the different NMSE-NSDav combinations were found and the optimal trade-off from optimized reconstruction parameters corresponded to a maximum AUC value. The 4D MAP-RBI-EM with ADS correction, which had the best trade-off among the tested reconstruction methods, also had the highest AUC value, resulting in significantly better human observer detection performance when detecting regional myocardial wall motion abnormality. We concluded that the NMSE-NSDav trade-off was shown to agree with observer performance for the detection task of the regional motion abnormality, and the optimized 4D MAP-RBI-EM method with ADS corrections provides significant improvement compared to 3D FBP and 3D OS-EM with ADS corrections in detecting regional myocardial wall motion abnormali in 4D gated MP SPECT.

Chances and limitations of non‐invasive tests in the assessment of liver fibrosis in liver transplant patients

Because fibrosis progression resulting in liver cirrhosis represents the main reason for graft lost in patients after liver transplantation, an early detection of liver fibrosis is crucial. In recent years, several non-invasive tests for the assessment of liver fibrosis have been developed. We prospectively assessed the stage of liver fibrosis of 135 liver transplant patients (94 hepatitis C virus [HCV], 41 alcoholic cirrhosis) using liver biopsy, transient elastography, and serum markers. In the HCV group, the area under the receiver operating characteristic curve (AUROC) for diagnosis of significant fibrosis (F ≥ 2) and cirrhosis (F = 4) was 0.81 (negative predictive value [NPV] = 0.58, positive predictive value [PPV] = 0.9) and 0.87 (NPV = 0.94, PPV = 0.56), respectively. In the alcoholic cirrhosis group, significant fibrosis (F ≥ 2) was diagnosed with an AUROC of 0.83 (NPV = 1.00, PPV = 0.23). In both groups, higher AUROC values were reached in patients with a body mass index of <25 kg/m(2) , and both serum markers showed no significant correlation to liver fibrosis. The transient elastography is a reliable test for exclusion of liver cirrhosis in HCV transplant and significant liver fibrosis in alcoholic transplant patients. For the diagnosis of significant liver fibrosis in HCV transplant patients, the transient elastography reaches good results but cannot replace liver biopsy. Both serum markers AST-to-platelet ratio index and FIB-4 are not feasible to assess liver fibrosis in liver transplant patients.