scholarly journals The Feature Ambiguity Mitigate Operator model helps improve bone fracture detection on X-ray radiograph

2021 ◽  
Vol 11 (1) ◽  
Author(s):  
Hui-Zhao Wu ◽  
Li-Feng Yan ◽  
Xiao-Qing Liu ◽  
Yi-Zhou Yu ◽  
Zuo-Jun Geng ◽  
...  
Keyword(s):  
Bone Fracture ◽  
Operating Characteristic ◽  
Characteristic Curve ◽  
Model Performance ◽  
Body Part ◽  
Controlled Experiment ◽  
Body Parts ◽  
Fracture Detection ◽  
Sensitivity Specificity ◽  
Fracture Level

AbstractThis study was performed to propose a method, the Feature Ambiguity Mitigate Operator (FAMO) model, to mitigate feature ambiguity in bone fracture detection on radiographs of various body parts. A total of 9040 radiographic studies were extracted. These images were classified into several body part types including 1651 hand, 1302 wrist, 406 elbow, 696 shoulder, 1580 pelvic, 948 knee, 1180 ankle, and 1277 foot images. Instance segmentation was annotated by radiologists. The ResNext-101+FPN was employed as the baseline network structure and the FAMO model for processing. The proposed FAMO model and other ablative models were tested on a test set of 20% total radiographs in a balanced body part distribution. To the per-fracture extent, an AP (average precision) analysis was performed. For per-image and per-case, the sensitivity, specificity, and AUC (area under the receiver operating characteristic curve) were analyzed. At the per-fracture level, the controlled experiment set the baseline AP to 76.8% (95% CI: 76.1%, 77.4%), and the major experiment using FAMO as a preprocessor improved the AP to 77.4% (95% CI: 76.6%, 78.2%). At the per-image level, the sensitivity, specificity, and AUC were 61.9% (95% CI: 58.7%, 65.0%), 91.5% (95% CI: 89.5%, 93.3%), and 74.9% (95% CI: 74.1%, 75.7%), respectively, for the controlled experiment, and 64.5% (95% CI: 61.3%, 67.5%), 92.9% (95% CI: 91.0%, 94.5%), and 77.5% (95% CI: 76.5%, 78.5%), respectively, for the experiment with FAMO. At the per-case level, the sensitivity, specificity, and AUC were 74.9% (95% CI: 70.6%, 78.7%), 91.7%% (95% CI: 88.8%, 93.9%), and 85.7% (95% CI: 84.8%, 86.5%), respectively, for the controlled experiment, and 77.5% (95% CI: 73.3%, 81.1%), 93.4% (95% CI: 90.7%, 95.4%), and 86.5% (95% CI: 85.6%, 87.4%), respectively, for the experiment with FAMO. In conclusion, in bone fracture detection, FAMO is an effective preprocessor to enhance model performance by mitigating feature ambiguity in the network.

Predicting 1p/19q codeletion status using diffusion-, susceptibility-, perfusion-weighted, and conventional MRI in IDH-mutant lower-grade gliomas

2020 ◽  
pp. 028418512097362
Author(s):  
Xiefeng Yang ◽  
Yu Lin ◽  
Zhen Xing ◽  
Dejun She ◽  
Yan Su ◽  
...  
Keyword(s):  
Predictive Value ◽  
Operating Characteristic ◽  
Cerebral Blood Volume ◽  
Characteristic Curve ◽  
Lower Grade ◽  
Dynamic Susceptibility ◽  
Dynamic Susceptibility Contrast ◽  
Conventional Mri ◽  
Susceptibility Contrast ◽  
Sensitivity Specificity

Background Isocitrate dehydrogenase (IDH)-mutant lower-grade gliomas (LGGs) are further classified into two classes: with and without 1p/19q codeletion. IDH-mutant and 1p/19q codeleted LGGs have better prognosis compared with IDH-mutant and 1p/19q non-codeleted LGGs. Purpose To evaluate conventional magnetic resonance imaging (cMRI), diffusion-weighted imaging (DWI), susceptibility-weighted imaging (SWI), and dynamic susceptibility contrast perfusion-weighted imaging (DSC-PWI) for predicting 1p/19q codeletion status of IDH-mutant LGGs. Material and Methods We retrospectively reviewed cMRI, DWI, SWI, and DSC-PWI in 142 cases of IDH mutant LGGs with known 1p/19q codeletion status. Features of cMRI, relative ADC (rADC), intratumoral susceptibility signals (ITSSs), and the value of relative cerebral blood volume (rCBV) were compared between IDH-mutant LGGs with and without 1p/19q codeletion. Receiver operating characteristic curve and logistic regression were used to determine diagnostic performances. Results IDH-mutant and 1p/19q non-codeleted LGGs tended to present with the T2/FLAIR mismatch sign and distinct borders ( P < 0.001 and P = 0.038, respectively). Parameters of rADC, ITSSs, and rCBVmax were significantly different between the 1p/19q codeleted and 1p/19q non-codeleted groups ( P < 0.001, P = 0.017, and P < 0.001, respectively). A combination of cMRI, SWI, DWI, and DSC-PWI for predicting 1p/19q codeletion status in IDH-mutant LGGs resulted in a sensitivity, specificity, positive predictive value, negative predictive value, and an AUC of 80.36%, 78.57%, 83.30%, 75.00%, and 0.88, respectively. Conclusion 1p/19q codeletion status of IDH-mutant LGGs can be stratified using cMRI and advanced MRI techniques, including DWI, SWI, and DSC-PWI. A combination of cMRI, rADC, ITSSs, and rCBVmax may improve the diagnostic performance for predicting 1p/19q codeletion status.

scholarly journals Feasibility and Validity of Computed Tomography-Derived Fractional Flow Reserve in Patients With Severe Aortic Stenosis

2020 ◽  
Author(s):  
Michael Michail ◽  
Abdul-Rahman Ihdayhid ◽  
Andrea Comella ◽  
Udit Thakur ◽  
James D. Cameron ◽  
...  
Keyword(s):  
Aortic Stenosis ◽  
Diagnostic Accuracy ◽  
Operating Characteristic ◽  
Severe Aortic Stenosis ◽  
Characteristic Curve ◽  
Fractional Flow ◽  
Predictive Values ◽  
Flow Reserve ◽  
Artery Disease ◽  
Sensitivity Specificity

Background: Coronary artery disease is common in patients with severe aortic stenosis. Computed tomography-derived fractional flow reserve (CT-FFR) is a clinically used modality for assessing coronary artery disease, however, its use has not been validated in patients with severe aortic stenosis. This study assesses the safety, feasibility, and validity of CT-FFR in patients with severe aortic stenosis. Methods: Prospectively recruited patients underwent standard-protocol invasive FFR and coronary CT angiography (CTA). CTA images were analyzed by central core laboratory (HeartFlow, Inc) for independent evaluation of CT-FFR. CT-FFR data were compared with FFR (ischemia defined as FFR ≤0.80). Results: Forty-two patients (68 vessels) underwent FFR and CTA; 39 patients (92.3%) and 60 vessels (88.2%) had interpretable CTA enabling CT-FFR computation. Mean age was 76.2±6.7 years (71.8% male). No patients incurred complications relating to premedication, CTA, or FFR protocol. Mean FFR and CT-FFR were 0.83±0.10 and 0.77±0.14, respectively. CT calcium score was 1373.3±1392.9 Agatston units. On per vessel analysis, there was positive correlation between FFR and CT-FFR (Pearson correlation coefficient, R =0.64, P <0.0001). Sensitivity, specificity, positive predictive value, and negative predictive values were 73.9%, 78.4%, 68.0%, and 82.9%, respectively, with 76.7% diagnostic accuracy. The area under the receiver-operating characteristic curve for CT-FFR was 0.83 (0.72–0.93, P <0.0001), which was higher than that of CTA and quantitative coronary angiography ( P =0.01 and P <0.001, respectively). Bland-Altman plot showed mean bias between FFR and CT-FFR as 0.059±0.110. On per patient analysis, the sensitivity, specificity, positive predictive, and negative predictive values were 76.5%, 77.3%, 72.2%, and 81.0% with 76.9% diagnostic accuracy. The per patient area under the receiver-operating characteristic curve analysis was 0.81 (0.67–0.95, P <0.0001). Conclusions: CT-FFR is safe and feasible in patients with severe aortic stenosis. Our data suggests that the diagnostic accuracy of CT-FFR in this cohort potentially enables its use in clinical practice and provides the foundation for future research into the use of CT-FFR for coronary evaluation pre-aortic valve replacement.

scholarly journals Utility of Thrombin Time in Management of Patients with Green Pit Vipers Bite

2020 ◽  
Vol 8 ◽  
pp. 205031212096646
Author(s):  
Achara Tongpoo ◽  
Pimjai Niparuck ◽  
Charuwan Sriapha ◽  
Winai Wananukul ◽  
Satariya Trakulsrichai
Keyword(s):  
Positive Predictive Value ◽  
Predictive Value ◽  
Operating Characteristic ◽  
Fibrinogen Level ◽  
Characteristic Curve ◽  
International Normalized Ratio ◽  
Thrombin Time ◽  
Coagulation Tests ◽  
Sensitivity Specificity ◽  
Gold Standards

Objectives: GGreen pit vipers (GPV) envenomation causes consumptive coagulopathy mainly by thrombin-like enzymes. Fibrinogen levels are generally investigated to help evaluate systemic envenomation. However, tests of fibrinogen levels may not be available in every hospital. This study aimed to determine the sensitivity, specificity and accuracy for a range of various coagulation tests (20 minute whole blood clotting test (20WBCT), prothrombin time, international normalized ratio and thrombin time (TT)), comparing to the two gold standards performed in patients with GPV bite. Methods: This was the pilot study which we retrospectively reviewed fibrinogen level results including the hospital records of 24 GPV ( Trimeresurus albolabris or macrops) bite patients visiting Ramathibodi Hospital, Thailand during 2013–2017 with 65 results of fibrinogen levels. The fibrinogen levels <164 and <100 mg/dL were used as the standard cut-off points or gold standards as the abnormal low and critical levels, respectively. Results: Most were male. All had local effects. For fibrinogen levels <164 and <100 mg/dL, prolonged TT had the highest sensitivity of 57.1% and 82.4%; the negative predictive value of 74.5% and 93.6%; the accuracy of 81.0% and 92.1%; and the area under a receiver operating characteristic curve of 0.762 and 0.873, respectively. For fibrinogen levels <164, unclotted 20WBCT and prolonged TT had the highest specificity and positive predictive value of 100% all. For fibrinogen levels <100, unclotted 20WBCT had the highest specificity and positive predictive value of 100% both, while prolonged TT had the specificity and positive predictive value of 95.7% and 87.5%, respectively. One patient developed isolated thrombocytopenia without hypofibrinogenemia and coagulopathy. Conclusions: Among four coagulation tests, TT was the most sensitive and accurate test to indicate hypofibrinogenemia in GPV bite patients. In case of unavailable fibrinogen levels thrombin time might be investigated to help evaluate patients’ fibrinogen status. Isolated thrombocytopenia could occur in GPV envenomation.

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.

scholarly journals Diagnostic accuracy of a urine dipstick for detecting albuminuria in hypertensive patients

F1000Research ◽  
2021 ◽  
Vol 9 ◽  
pp. 1244
Author(s):  
Phornwipa Panta ◽  
Win Techakehakij
Keyword(s):  
Diagnostic Accuracy ◽  
Predictive Value ◽  
Operating Characteristic ◽  
Characteristic Curve ◽  
Hypertensive Patients ◽  
Spot Urine ◽  
Urine Dipstick ◽  
Urine Albumin ◽  
Low Sensitivity ◽  
Sensitivity Specificity

Background: Screening for albuminuria is generally recommended among patients with hypertension. While the urine dipstick is commonly used for screening urine albumin, there is little evidence about its diagnostic accuracy among these patients in Thailand. This study aimed to assess the diagnostic accuracy of a dipstick in Thai hypertensive patients for detecting albuminuria. Methods: This study collected the data of 3,067 hypertensive patients, with the results of urine dipstick and urine albumin-to-creatinine ratio (ACR) from random single spot urine being examined in the same day at least once, at Lampang Hospital, Thailand, during 2018. For ACR, a reference standard of ≥ 30 mg/g was applied to indicate the presence of albuminuria. Results: The sensitivity, specificity, positive predictive value (PPV), and negative predictive value of the trace result from dipsticks were 53.6%, 94.5%, 86.5%, and 75.5%, respectively. The area under the receiver operating characteristic curve of the dipstick was 0.748. Conclusion: Using the dipstick for screening albuminuria among hypertensive patients should not be recommended for mass screening due to its low sensitivity. In response to high PPV, a trace threshold of the dipstick may be used to indicate presence of albuminuria.

scholarly journals Diagnostic accuracy of a urine dipstick for detecting albuminuria in hypertensive patients

F1000Research ◽  
2020 ◽  
Vol 9 ◽  
pp. 1244
Author(s):  
Phornwipa Panta ◽  
Win Techakehakij
Keyword(s):  
Diagnostic Accuracy ◽  
Predictive Value ◽  
Operating Characteristic ◽  
Characteristic Curve ◽  
Hypertensive Patients ◽  
Spot Urine ◽  
Urine Dipstick ◽  
Urine Albumin ◽  
Low Sensitivity ◽  
Sensitivity Specificity

Background: Screening for albuminuria is generally recommended among patients with hypertension. While the urine dipstick is commonly used for screening urine albumin, there is little evidence about its diagnostic accuracy among these patients. This study aimed to assess the diagnostic accuracy of a dipstick in Thai hypertensive patients for detecting albuminuria. Methods: This study collected the data of 3,067 hypertensive patients, with the results of urine dipstick and urine albumin-to-creatinine ratio (ACR) from random single spot urine being examined in the same day at least once, at Lampang Hospital, Thailand, during 2018. For ACR, a reference standard of ≥ 30 mg/g was applied to indicate the presence of albuminuria. Results: The sensitivity, specificity, positive predictive value (PPV), and negative predictive value of the trace result from dipsticks were 53.6%, 94.5%, 86.5%, and 75.5%, respectively. The area under the receiver operating characteristic curve of the dipstick was 0.748. Conclusion: Using the dipstick for screening albuminuria among hypertensive patients should not be recommended due to its low sensitivity. In response to high PPV, a trace threshold of the dipstick may be used to indicate presence of albuminuria.

Diagnostic value of HOX transcript antisense RNA for cancer detection: a meta-analysis

2020 ◽  
Vol 14 (5) ◽  
pp. 401-411
Author(s):  
Weihao Kong ◽  
Mingwei Yang ◽  
Yunfeng Zhu ◽  
Xiaomin Zuo ◽  
Hengyi Wang ◽  
...  
Keyword(s):  
Likelihood Ratio ◽  
Antisense Rna ◽  
Noncoding Rna ◽  
Operating Characteristic ◽  
Meta Analysis ◽  
Characteristic Curve ◽  
Positive Likelihood Ratio ◽  
Negative Likelihood Ratio ◽  
Diagnostic Odds Ratio ◽  
Sensitivity Specificity

Aim: Numerous studies have investigated the diagnostic role of long noncoding RNA HOX transcript antisense RNA in cancers, but its diagnostic efficacy is inconsistent. Methods: The PubMed, Embase, Web of Science and Cochrane Library databases are used to retrieve relevant studies. The bivariate effect model was used to compute the combined sensitivity, specificity, positive likelihood ratio, negative likelihood ratio, diagnostic odds ratio and area under the receiver operating characteristic curve. Results: A total of 13 studies were included in this meta-analysis. The combined sensitivity, specificity, positive likelihood ratio, negative likelihood ratio, diagnostic odds ratio and area under the receiver operating characteristic curve were: 0.77, 0.83, 4.7, 0.28, 17 and 0.87, respectively. Deeks’ funnel plot test (p = 0.103) indicated no publication bias. Conclusion: Long noncoding RNA HOX transcript antisense RNA may be a useful biomarker for cancer detection.

External Validation of Different Scoring Systems for Suspected Choledocholithiasis

2019 ◽  
Vol 36 (6) ◽  
pp. 530-538
Author(s):  
Nicolò Tamini ◽  
Davide Paolo Bernasconi ◽  
Luca Gianotti
Keyword(s):  
Operating Characteristic ◽  
Bile Duct Stone ◽  
Characteristic Curve ◽  
External Validation ◽  
Area Under The Curve ◽  
Scoring Systems ◽  
Youden Index ◽  
Predictive Values ◽  
Sensitivity Specificity ◽  
Symptoms And Signs

Aim of the Study: The diagnosis of choledocholithiasis is challenging. Previously published scoring systems designed to calculate the risk of choledocholithiasis were evaluated to appraise the diagnostic performance. Patients and Methods: Data of patients who were admitted between 2013 and 2015 with the following characteristics were retrieved: bile stone-related symptoms and signs, and indication to laparoscopic cholecystectomy. To validate and appraise the performance of the 6 scoring systems, the acknowledged domains of each metrics were applied to the present cohort. Sensitivity, specificity, positive, negative predictive, Youden index, and receiver operating characteristic curve with the area under the curve (AUC) values of the scores were calculated. Results: Two-hundred patients were analyzed. The highest sensitivity and specificity were obtained from the Menezes’ (96.6%) and Telem’s (99.3%) metrics respectively. The Telem’s and Menezes’ scores had the best positive (75.0%) and negative (96.4%) predictive values respectively. The best accuracy, as computed by the Youden index and AUC, was found for the Soltan’s scoring system (0.628 and 0.88, respectively). Conclusion: The available scoring systems are precise only in identifying patients with a negligible risk of common bile duct stone, but overall insufficiently accurate to suggest the routine use in clinical practice.

Clinical Evaluation of a Monoclonal Antibody-based Enzyme Immunoassay for Fibrin Degradation Products in Patients with Clinically Suspected Pulmonary Embolism

2000 ◽  
Vol 83 (06) ◽  
pp. 892-895 ◽  
Author(s):  
Wouter de Monyé ◽  
Jeroen Lijmer ◽  
Willem Nieuwenhuizen ◽  
Harry Büller ◽  
Menno Huisman ◽  
...  
Keyword(s):  
Pulmonary Embolism ◽  
Negative Predictive Value ◽  
Predictive Value ◽  
Operating Characteristic ◽  
Degradation Products ◽  
Characteristic Curve ◽  
Suspected Pulmonary Embolism ◽  
Fibrin Degradation Products ◽  
Potential Clinical Utility ◽  
Sensitivity Specificity

SummaryWe prospectively evaluated the diagnostic accuracy of the Fibrinostika® FbDP assay in 304 consecutive patients with suspected pulmonary embolism and examined potentially useful cut-off points at which the disease can be excluded. The prevalence of pulmonary embolism was 31%. The assay generated an area under the Receiver Operating Characteristic curve of 0.79 (95% CI 0.73–0.84). A cut-off point of 0.05 µ,g/ml yielded a sensitivity, specificity, negative predictive value and an exclusion efficiency of 100% (95% CI 96–100), 5% (95% CI 2–9), 100% (95% CI 69–100) and 3% (95% CI 2–6), respectively. A clinically useful cut-off point seems to be 0.11 µ,g/ml which corresponded with a sensitivity, specificity, negative predictive value and an exclusion efficiency of 96% (95% CI 90–99), 27% (95% CI 24–28), 93% (95% CI 84–98) and 20% (95% CI 16–25), respectively. We conclude that the assay has potential clinical utility for the exclusion of pulmonary embolism, but it cannot be used as a sole test.

scholarly journals Interleukin-27 as a Diagnostic Biomarker for Patients with Sepsis: A Meta-Analysis

2021 ◽  
Vol 2021 ◽  
pp. 1-7
Author(s):  
Ying Wang ◽  
Jingyi Zhao ◽  
Yinhui Yao ◽  
Dan Zhao ◽  
Shiquan Liu
Keyword(s):  
Receiver Operating Characteristic Curve ◽  
Receiver Operating Characteristic ◽  
Operating Characteristic ◽  
Meta Analysis ◽  
Characteristic Curve ◽  
Diagnostic Biomarker ◽  
Summary Receiver Operating Characteristic ◽  
Funnel Plot ◽  
Operating Characteristic Curve ◽  
Sensitivity Specificity

Background. The present study was aimed to investigate the value of blood interleukin-27 (IL-27) as a diagnostic biomarker of sepsis. Methods. We searched PubMed, EMBASE, the Cochrane Library, and the reference lists of relevant articles. All studies published up to October 21, 2020, which evaluated the accuracy of IL-27 levels for the diagnosis of sepsis were included. All the selected papers were assessed using the Quality Assessment of Diagnostic Accuracy Studies-2 (QUADAS-2). We used a bivariate random effects model to estimate sensitivity, specificity, diagnostic odds ratios (DOR), and a summary receiver operating characteristic curve (SROC). Deeks’ funnel plot was used to illustrate the potential presence of publication bias. Results. This meta-analysis included seven articles. The pooled sensitivity, specificity, and DOR were 0.85 (95% CI, 0.72-0.93), 0.72 (95% CI, 0.42-0.90), and 15 (95% CI, 3-72), respectively. The area under the summary receiver operating characteristic curve was 0.88 (95% CI, 0.84-0.90). The pooled I 2 statistic was 96.05 for the sensitivity and 96.65 for the specificity in the heterogeneity analysis. Deeks’ funnel plot indicated no publication bias in this meta-analysis ( P = 0.07 ). Conclusions. The present results showed that IL-27 is a reliable diagnostic biomarker of sepsis, but it should be investigated in combination with other clinical tests and results.

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