Abstract 3338: Value of a Novel Index of Microcirculatory Resistance for Invasively Assessing Myocardial Viability After Primary Angioplasty in Acute Myocardial Infarction: Comparison With FDG-PET

Circulation ◽  
2007 ◽  
Vol 116 (suppl_16) ◽  
Author(s):  
Hong-Seok Lim ◽  
Seung-Jea Tahk ◽  
Myeong-Ho Yoon ◽  
Seong-Ill Woo ◽  
Woon-Jung Choi ◽  
...  
Keyword(s):  
Flow Velocity ◽  
Myocardial Viability ◽  
Fdg Pet ◽  
Mean Transit Time ◽  
Area Under The Curve ◽  
Resistance Index ◽  
Primary Pci ◽  
Operating Characteristics ◽  
Fdg Uptake ◽  
Index Of Microcirculatory Resistance

Background: Despite the prognostic importance of the status of coronary microcirculation, there has been lacking in comparative studies on the most reliable invasive measurement for assessing microvascular integrity and myocardial viability in AMI. We compared a novel Index of Microcirculatory Resistance(IMR) to intracoronary wire-based physiologic parameters for evaluating myocardial viability after primary percutaneous coronary intervention(PCI) in AMI. Methods: After successful primary stenting for 28 patients with AMI, Doppler-derived microvascular resistance index (MVRI) and phasic flow velocity patterns were evaluated. Using a pressure-temperature sensor-tipped coronary wire, thermodilution-derived CFR(CFR thermo ) and coronary wedge pressure(P cw ) were measured and the ratio of P cw and mean aortic pressure(P cw /P a ) was calculated, along with IMR, defined as the distal coronary pressure divided by the inverse of the hyperemic mean transit time. 18 F-fluorodeoxyglucose(FDG) PET was performed after primary PCI to evaluate myocardial viability by regional percentage uptake of FDG in infarct-related segments. Results: Among Doppler-derived parameters, regional FDG uptake showed nice correlation with hyperemic averaged peak velocity(r=0.561, p=0.002), hyperemic MVRI (r= −0.452, p=0.016) and baseline deceleration time of diastolic flow velocity (r=0.505, p=0.006). In the group of pressure-derived parameters CFR thermo , P cw /P a and IMR revealed good correlations with regional FDG uptake (r=0.487, p=0.016; r= −0.469, p=0.012; r= −0.656, p<0.001, respectively). By the receiver operating characteristics curve analysis for prediction of myocardial viability, as defined by the 50% FDG-PET threshold value, the largest area under the curve was acquired by IMR and the best cut-off value of IMR for prediction of myocardial viability was 22U (sensitivity of 79%, specificity of 86% and accuracy of 81%). Conclusions: Wire-based coronary physiologic assessment is useful for the prediction of myocardial viability immediately after primary PCI. IMR, a novel index representing the microvascular integrity, is a reliable parameter for the invasive, on-site assessment of myocardial viability after primary PCI in AMI.

Continuous Versus Multiple Rapid Infusions of Indomethacin: Effects on Cerebral Blood Flow Velocity

PEDIATRICS ◽  
1995 ◽  
Vol 95 (2) ◽  
pp. 244-248 ◽  
Author(s):  
Cathy Hammerman ◽  
Joram Glaser ◽  
Michael S. Schimmel ◽  
Benjamin Ferber ◽  
Michael Kaplan ◽  
...  
Keyword(s):  
Blood Flow ◽  
Cerebral Blood Flow ◽  
Flow Velocity ◽  
Blood Flow Velocity ◽  
Cerebral Blood Flow Velocity ◽  
Ductus Arteriosus ◽  
Area Under The Curve ◽  
Resistance Index ◽  
Color Flow ◽  
Rapid Injection

Objective. Therapeutic administration of indomethacin for patent ductus arteriosus (PDA) closure has been documented to decrease cerebral blood flow velocity which may be harmful to the vulnerable premature neonate. We have therefore compared the effects of administering indomethacin by rapid injection versus slow, continuous indomethacin infusion at the same total therapeutic dose on middle cerebral artery (MCA) systolic and diastolic flow velocity, resistance index, and cerebral blood flow (as reflected by the integrated area under the curve). Methods. Premature neonates (&lt;1750 g) documented echocardiographically to have a PDA were randomized to receive indomethacin either by three rapid injection doses or by continuous intravenous infusion over the ensuing 36 hours, providing an equivalent total dose. Echocardiograms and transcranial color flow mapping of the MCA flow velocity were measured at baseline and serially following initiation of therapy in both groups. Effects on cerebral blood flow velocity are presented. Results. Eighteen infants [rapid injection-1.2 ± 0.3 kg (n = 9) and continuous-1.1 ± 0.2 kg (n = 9)] were studied. In the rapid injection treated infants decreased flow velocity in the MCA as manifested by abrupt, significant decreases in systolic (to 70 ± 8% baseline) and diastolic (to 65 ± 13% baseline) flow velocity and area under the curve (to 60 ± 10% of baseline) were evident by 4 minutes and progressed to 30 minutes after treatment initiation. These changes were not observed in the group treated with continuous indomethacin. Both therapeutic modalities were equally successful in closing the ductus, although the numbers are too small to definitively determine therapeutic efficacy. Conclusions. Slow, continuous infusion eliminated the decrease in cerebral flow velocity and appears to be effective in closing the PDA.

scholarly journals End-to-end convolutional neural network enables COVID-19 detection from breath and cough audio: a pilot study

2021 ◽  
Vol 7 (2) ◽  
pp. 356-362
Author(s):  
Harry Coppock ◽  
Alex Gaskell ◽  
Panagiotis Tzirakis ◽  
Alice Baird ◽  
Lyn Jones ◽  
...  
Keyword(s):  
Neural Network ◽  
Convolutional Neural Network ◽  
Low Cost ◽  
Area Under The Curve ◽  
Alternative Form ◽  
Economic Damage ◽  
Audio Signals ◽  
Operating Characteristics ◽  
Data Set ◽  
Empirical Performance

BackgroundSince the emergence of COVID-19 in December 2019, multidisciplinary research teams have wrestled with how best to control the pandemic in light of its considerable physical, psychological and economic damage. Mass testing has been advocated as a potential remedy; however, mass testing using physical tests is a costly and hard-to-scale solution.MethodsThis study demonstrates the feasibility of an alternative form of COVID-19 detection, harnessing digital technology through the use of audio biomarkers and deep learning. Specifically, we show that a deep neural network based model can be trained to detect symptomatic and asymptomatic COVID-19 cases using breath and cough audio recordings.ResultsOur model, a custom convolutional neural network, demonstrates strong empirical performance on a data set consisting of 355 crowdsourced participants, achieving an area under the curve of the receiver operating characteristics of 0.846 on the task of COVID-19 classification.ConclusionThis study offers a proof of concept for diagnosing COVID-19 using cough and breath audio signals and motivates a comprehensive follow-up research study on a wider data sample, given the evident advantages of a low-cost, highly scalable digital COVID-19 diagnostic tool.

scholarly journals Association of transcranial Doppler blood flow velocity slow waves with delayed cerebral ischemia in patients suffering from subarachnoid hemorrhage: a retrospective study

2021 ◽  
Vol 9 (1) ◽  
Author(s):  
Vasilios E. Papaioannou ◽  
Karol P. Budohoski ◽  
Michal M. Placek ◽  
Zofia Czosnyka ◽  
Peter Smielewski ◽  
...  
Keyword(s):  
Blood Flow ◽  
Subarachnoid Hemorrhage ◽  
Cerebral Ischemia ◽  
Flow Velocity ◽  
Transcranial Doppler ◽  
Blood Flow Velocity ◽  
Cerebral Blood Flow Velocity ◽  
Delayed Cerebral Ischemia ◽  
Area Under The Curve ◽  
Slow Waves

Abstract Background Cerebral vasospasm (VS) and delayed cerebral ischemia (DCI) constitute major complications following subarachnoid hemorrhage (SAH). A few studies have examined the relationship between different indices of cerebrovascular dynamics with the occurrence of VS. However, their potential association with the development of DCI remains elusive. In this study, we investigated the pattern of changes of different transcranial Doppler (TCD)-derived indices of cerebrovascular dynamics during vasospasm in patients suffering from subarachnoid hemorrhage, dichotomized by the presence of delayed cerebral ischemia. Methods A retrospective analysis was performed using recordings from 32 SAH patients, diagnosed with VS. Patients were divided in two groups, depending on development of DCI. Magnitude of slow waves (SWs) of cerebral blood flow velocity (CBFV) was measured. Cerebral autoregulation was estimated using the moving correlation coefficient Mxa. Cerebral arterial time constant (tau) was expressed as the product of resistance and compliance. Complexity of CBFV was estimated through measurement of sample entropy (SampEn). Results In the whole population (N = 32), magnitude of SWs of ipsilateral to VS side CBFV was higher during vasospasm (4.15 ± 1.55 vs before: 2.86 ± 1.21 cm/s, p < 0.001). Ipsilateral SWs of CBFV before VS had higher magnitude in DCI group (N = 19, p < 0.001) and were strongly predictive of DCI, with area under the curve (AUC) = 0.745 (p = 0.02). Vasospasm caused a non-significant shortening of ipsilateral values of tau and increase in SampEn in all patients related to pre-VS measurements, as well as an insignificant increase of Mxa in DCI related to non-DCI group (N = 13). Conclusions In patients suffering from subarachnoid hemorrhage, TCD-detected VS was associated with higher ipsilateral CBFV SWs, related to pre-VS measurements. Higher CBFV SWs before VS were significantly predictive of delayed cerebral ischemia.

scholarly journals Multi-scale characterizations of colon polyps via computed tomographic colonography

2019 ◽  
Vol 2 (1) ◽  
Author(s):  
Weiguo Cao ◽  
Marc J. Pomeroy ◽  
Yongfeng Gao ◽  
Matthew A. Barish ◽  
Almas F. Abbasi ◽  
...  
Keyword(s):  
Area Under The Curve ◽  
Texture Features ◽  
Learning Model ◽  
Colon Polyps ◽  
Texture Descriptor ◽  
Operating Characteristics ◽  
Computed Tomographic ◽  
Multi Scale ◽  
Definition Of ◽  
Occurrence Matrix

AbstractTexture features have played an essential role in the field of medical imaging for computer-aided diagnosis. The gray-level co-occurrence matrix (GLCM)-based texture descriptor has emerged to become one of the most successful feature sets for these applications. This study aims to increase the potential of these features by introducing multi-scale analysis into the construction of GLCM texture descriptor. In this study, we first introduce a new parameter - stride, to explore the definition of GLCM. Then we propose three multi-scaling GLCM models according to its three parameters, (1) learning model by multiple displacements, (2) learning model by multiple strides (LMS), and (3) learning model by multiple angles. These models increase the texture information by introducing more texture patterns and mitigate direction sparsity and dense sampling problems presented in the traditional Haralick model. To further analyze the three parameters, we test the three models by performing classification on a dataset of 63 large polyp masses obtained from computed tomography colonoscopy consisting of 32 adenocarcinomas and 31 benign adenomas. Finally, the proposed methods are compared to several typical GLCM-texture descriptors and one deep learning model. LMS obtains the highest performance and enhances the prediction power to 0.9450 with standard deviation 0.0285 by area under the curve of receiver operating characteristics score which is a significant improvement.

scholarly journals Diagnostic work up of anemic patients: role of iron deficiency

2020 ◽  
Vol 0 (0) ◽  
Author(s):  
Daniela Meiser ◽  
Lale Kayikci ◽  
Matthias Orth
Keyword(s):  
Iron Deficiency ◽  
Complete Blood Count ◽  
Iron Status ◽  
Area Under The Curve ◽  
Diagnostic Value ◽  
Diagnostic Tools ◽  
Operating Characteristics ◽  
Inflammatory Conditions ◽  
Reliable Parameter ◽  
Work Up

AbstractObjectivesDiagnosing disturbances in iron metabolism can be challenging when accompanied by inflammation. New diagnostic tools such as the “Thomas-plot” (TP) (relation of soluble transferrin receptor [sTfR]/log ferritin to reticulocyte hemoglobin content [RET-He]) were established to improve classification of anemias. Aim of this retrospective study was to assess the added diagnostic value of the TP in anemia work up.MethodsPatients from December 2016 to September 2018 with a complete blood count, iron status, RET-He and sTfR were manually classified into the four quadrants of the TP on basis of conventional iron markers. Manual and algorithm-based classifications were compared using cross tabulations, Box–Whisker-Plots as well as Receiver-Operating-Characteristics (ROC) to calculate the diagnostic accuracy using Area under the Curve (AUC) analysis.ResultsA total of 3,745 patients with a conventional iron status, including 1,721 TPs, could be evaluated. In 70% of the cases the manual classification was identical to the TP, in 10% it was deviant. 20% could not clearly be classified, mostly due to inflammatory conditions. In the absence of an inflammatory condition, ferritin was a reliable parameter to define iron deficiency (ID) (AUC 0.958). In the presence of inflammation, the significance of the ferritin index (AUC 0.917) and of the RET-He (AUC 0.957) increased.ConclusionsThe TP can be useful for narrowing down the causes of anemia in complex cases. Further studies with focus on special patient groups, e.g., oncological or rheumatic patients, are desirable.

scholarly journals Quantitative analysis of myocardial metabolic heterogeneity is superior to visual assessment for the detection of active cardiac sarcoidosis by F-18 FDG PET-CT imaging

2021 ◽  
Vol 22 (Supplement_1) ◽  
Author(s):  
M Malik ◽  
M Yazdani ◽  
SM Gould ◽  
E Reyes
Keyword(s):  
Fdg Pet ◽  
Cardiac Sarcoidosis ◽  
Visual Assessment ◽  
Ct Imaging ◽  
Myocardial Inflammation ◽  
Fdg Uptake ◽  
Pet Ct ◽  
Metabolic Heterogeneity ◽  
Fdg Pet Ct

Abstract Funding Acknowledgements Type of funding sources: None. Background Myocardial inflammation may occur in the context of a multisystem disease such as sarcoidosis, adversely affecting prognosis. A definitive diagnosis of cardiac sarcoidosis (CS) is essential to implementing life-saving treatment but this is complicated by the invasive nature of endomyocardial biopsy (EMB) and its low accuracy. Positron emission tomography (PET) assists in diagnosis, which relies on visual interpretation of myocardial F-18 FDG uptake. The value of quantitative analysis and its application to clinical practice remain uncertain. Purpose To investigate the power of quantitative F-18 FDG PET-CT imaging analysis for detecting CS in patients with suspected disease. Methods All patients underwent F-18 FDG PET-CT after a 24-hour low-carbohydrate diet and 15-hour fasting as part of their diagnostic work-up for suspected cardiac inflammation. Cardiovascular magnetic resonance acted as gatekeeper to PET-CT in 8 of every 10 scans. Myocardial F-18 FDG uptake was assessed qualitatively and quantitatively using both manually drawn regions of interest and automatic polar maps to measure global and segmental standardised F-18 FDG uptake values (SUV).  The coefficient of variation (CoV) was calculated to determine uptake heterogeneity. To confirm diagnosis, follow-up data regarding disease progression, further testing and treatment were collected. To allow for sufficient follow-up time, the first 40 consecutive patients from a prospective registry (n= 214; Sep 2017-Jun 2020) were included. Results A comprehensive clinical picture was obtained successfully in 37 patients (median [IQR], 17 [13.5] months) and a final diagnosis of CS reached in 7 (disease prevalence, 19%). EMB was performed in 2 patients only while 3 underwent PPM/ICD implantation. Significant predictors of CS were fulfilment of Japanese Ministry of Health and Welfare criteria (Wald, 6.44; p = 0.01) and left ventricular dysfunction (Wald 6.72; p = 0.01). Qualitative F-18 FDG PET-CT had a high negative (95%) but low positive (45%) predictive value for CS (sensitivity, 83%; specificity, 77%). F-18 FDG SUV CoV was the strongest imaging predictor (Wald, 6.77; p = 0.009) and was significantly higher in CS than non-CS (CoV median [quartiles], 0.26 [0.21, 0.36] and 0.12 [0.11, 0.14] respectively; p = 0.004). As per ROC curve analysis (AUC, 0.84), a CoV threshold of 0.20 was highly specific (93%) and sensitive (86%) for CS. Conclusion In a referring population with a low prevalence of cardiac sarcoidosis, F-18 FDG PET-CT imaging is sensitive for the detection of myocardial inflammation with active disease unlikely in patients with a negative scan. Quantitative evaluation of metabolic heterogeneity within the myocardium provides a strong, independent marker of active disease and should be considered alongside visual assessment.

scholarly journals New screening approach to detecting congenital syphilis in China: a retrospective cohort study

2020 ◽  
pp. archdischild-2020-320549
Author(s):  
Fang Hu ◽  
Shuai-Jun Guo ◽  
Jian-Jun Lu ◽  
Ning-Xuan Hua ◽  
Yan-Yan Song ◽  
...  
Keyword(s):  
Predictive Value ◽  
Congenital Syphilis ◽  
Area Under The Curve ◽  
Diagnostic Tools ◽  
Operating Characteristics ◽  
Loss To Follow Up ◽  
Sensitivity Specificity ◽  
Mother To Child ◽  
Rule Out

BackgroundDiagnosis of congenital syphilis (CS) is not straightforward and can be challenging. This study aimed to evaluate the validity of an algorithm using timing of maternal antisyphilis treatment and titres of non-treponemal antibody as predictors of CS.MethodsConfirmed CS cases and those where CS was excluded were obtained from the Guangzhou Prevention of Mother-to-Child Transmission of syphilis programme between 2011 and 2019. We calculated sensitivity, specificity, positive predictive value (PPV) and negative predictive value (NPV) using receiver operating characteristics (ROC) in two situations: (1) receiving antisyphilis treatment or no-treatment during pregnancy and (2) initiating treatment before 28 gestational weeks (GWs), initiating after 28 GWs or receiving no treatment for syphilis seropositive women.ResultsAmong 1558 syphilis-exposed children, 39 had confirmed CS. Area under the curve, sensitivity and specificity of maternal non-treponemal titres before treatment and treatment during pregnancy were 0.80, 76.9%, 78.7% and 0.79, 69.2%, 88.7%, respectively, for children with CS. For the algorithm, ROC results showed that PPV and NPV for predicting CS were 37.3% and 96.4% (non-treponemal titres cut-off value 1:8 and no antisyphilis treatment), 9.4% and 100% (non-treponemal titres cut-off value 1:16 and treatment after 28 GWs), 4.2% and 99.5% (non-treponemal titres cut-off value 1:32 and treatment before 28 GWs), respectively.ConclusionsAn algorithm using maternal non-treponemal titres and timing of treatment during pregnancy could be an effective strategy to diagnose or rule out CS, especially when the rate of loss to follow-up is high or there are no straightforward diagnostic tools.

scholarly journals Traumatic myositis ossificans: multifocal lesions suggesting malignancy on FDG-PET/CT—a case report

2020 ◽  
Vol 50 (1) ◽  
pp. 249-254
Author(s):  
Miho Sasaki ◽  
Yuka Hotokezaka ◽  
Reiko Ideguchi ◽  
Masataka Uetani ◽  
Shuichi Fujita
Keyword(s):  
Case Report ◽  
Fdg Pet ◽  
Myositis Ossificans ◽  
Whole Body ◽  
Left Cheek ◽  
Multiple Fractures ◽  
Fdg Uptake ◽  
Pet Ct ◽  
Multiple Regions ◽  
Fdg Pet Ct

AbstractMyositis ossificans (MO) is a benign soft-tissue lesion characterized by the heterotopic formation of the bone in skeletal muscles, usually due to trauma. MO is occasionally difficult to diagnose because of its clinical and radiological similarities with malignancy. We report a case of traumatic MO (TMO) in the masseter and brachial muscles of a 37-year-old man who presented with painless swelling in the left cheek and severe trismus. Due to the absence of a traumatic history at the first consultation and identification of a tumorous lesion in the left masseter muscle by magnetic resonance imaging (MRI), the lesion was suspected to be a malignant tumor. Subsequently, 18F-fluorodeoxyglucose positron-emission tomography/computed tomography (FDG-PET/CT) showed multiple regions of high FDG uptake across the whole body, suggestive of multiple metastases or other systemic diseases. However, intramuscular calcifications were also observed in the left masseter and brachial muscles, overlapping the areas with high FDG uptake. Moreover, multiple fractures were seen in the rib and lumbar spine, also overlapping the areas with high FDG uptake. Based on these imaging findings, along with a history of jet-ski trauma, TMO was suspected. The left cheek mass was surgically excised and histologically diagnosed as TMO. In this case report, FDG-PET/CT could detect multiple TMOs across the whole body. To the best of our knowledge, cases of multiple TMOs located far apart in different muscles are rare, and this may be the first report.

First trimester prediction of maternal glycemic status

2015 ◽  
Vol 43 (3) ◽  
Author(s):  
Rinat Gabbay-Benziv ◽  
Lauren E. Doyle ◽  
Miriam Blitzer ◽  
Ahmet A. Baschat
Keyword(s):  
Risk Score ◽  
Predictive Value ◽  
Challenge Test ◽  
Area Under The Curve ◽  
First Trimester ◽  
Tolerance Test ◽  
Oral Glucose ◽  
Operating Characteristics ◽  
Maternal Characteristics ◽  
Predictive Algorithm

AbstractTo predict gestational diabetes mellitus (GDM) or normoglycemic status using first trimester maternal characteristics.We used data from a prospective cohort study. First trimester maternal characteristics were compared between women with and without GDM. Association of these variables with sugar values at glucose challenge test (GCT) and subsequent GDM was tested to identify key parameters. A predictive algorithm for GDM was developed and receiver operating characteristics (ROC) statistics was used to derive the optimal risk score. We defined normoglycemic state, when GCT and all four sugar values at oral glucose tolerance test, whenever obtained, were normal. Using same statistical approach, we developed an algorithm to predict the normoglycemic state.Maternal age, race, prior GDM, first trimester BMI, and systolic blood pressure (SBP) were all significantly associated with GDM. Age, BMI, and SBP were also associated with GCT values. The logistic regression analysis constructed equation and the calculated risk score yielded sensitivity, specificity, positive predictive value, and negative predictive value of 85%, 62%, 13.8%, and 98.3% for a cut-off value of 0.042, respectively (ROC-AUC – area under the curve 0.819, CI – confidence interval 0.769–0.868). The model constructed for normoglycemia prediction demonstrated lower performance (ROC-AUC 0.707, CI 0.668–0.746).GDM prediction can be achieved during the first trimester encounter by integration of maternal characteristics and basic measurements while normoglycemic status prediction is less effective.

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