Cardiac magnetic field map topology quantified by Kullback-Leibler entropy identifies patients with hypertrophic cardiomyopathy

Hypertrophic cardiomyopathy (HCM) is a common primary inherited cardiac muscle disorder, defined clinically by the presence of unexplained left ventricular hypertrophy. The detection of affected patients remains challenging. Genetic testing is limited because only in 50%-60% of all HCM diagnoses an underlying mutation can be found. Furthermore, the disease has a varied clinical course and outcome, with many patients having little or no discernible cardiovascular symptoms, whereas others develop profound exercise limitation and recurrent arrhythmias or sudden cardiac death. Therefore prospective screening of HCM family members is strongly recommended. According to the current guidelines this includes serial echocardiographic and electrocardiographic examinations. In this study we investigated the capability of cardiac magnetic field mapping (CMFM) to detect patients suffering from HCM. We introduce for the first time a combined diagnostic approach based on map topology quantification using Kullback-Leibler (KL) entropy and regional magnetic field strength parameters. The cardiac magnetic field was recorded over the anterior chest wall using a multichannel-LT-SQUID system. CMFM was calculated based on a regular 36 point grid. We analyzed CMFM in patients with confirmed diagnosis of HCM (HCM, n=33, 43.8+/-13 years, 13 women, 20 men), a control group of healthy subjects (NORMAL, n=57, 39.6+/-8.9 years; 22 women and 35 men), and patients with confirmed cardiac hypertrophy due to arterial hypertension (HYP, n=42, 49.7+/-7.9 years, 15 women and 27 men). A subgroup analysis was performed between HCM patients suffering from the obstructive (HOCM, n=19) and nonobstructive (HNCM, n=14) form of the disease. KL entropy based map topology quantification alone identified HCM patients with a sensitivity of 78.8% and specificity of 86.9% (overall classification rate 84.8%). The combination of the KL parameters with a regional field strength parameter improved the overall classification rate to 87.9% (sensitivity: 84.8%, specificity: 88.9%, area under ROC curve: 0.94). KL measures applied to discriminate between HOCM and HNCM patients showed a correct classification of 78.8%. The combination of one KL and one regional parameter again improved the overall classification rate to 97%. A preliminary prospective analysis in two HCM families showed the feasibility of this diagnostic approach with a correct diagnosis of all 22 screened family members (1 HOCM, 4 HNCM, 17 normal). In conclusion, Cardiac Magnetic Field Mapping including KL entropy based topology quantifications is a suitable tool for HCM screening.     

Characterization of cardiac-related noise in fMRI of the cervical spinal cord

Magnetic resonance imaging (MRI) has recently been applied to study spinal cord function in humans. However, spinal functional MRI (fMRI) encounters major technical challenges with cardiac noise being considered a major source of noise. The present study relied on echo-planar imaging of the cervical cord at short TR (TR=250 ms; TE=40 ms; flip=45 degrees), combined with plethysmographic recordings to characterize the spatiotemporal properties of cardiac-induced signal changes in spinal fMRI. Frequency-based analyses examining signal change at the cardiac frequency confirmed mean fluctuations of about 10% (relative to the mean signal) in the spinal cord and surrounding cerebrospinal fluid (CSF), with maximal responses reaching up to 66% in some voxels. A spatial independent component analysis (sICA) confirmed that cardiac noise is an important source of variance in spinal fMRI with several components showing a response coherent with the cardiac frequency spectrum. The time course of the main cardiac components approximated a sinusoidal function tightly coupled to the cardiac systole with at least one component showing a comparable temporal profile across runs and subjects. Spatially, both the frequency-domain analysis and the sICA demonstrated cardiac noise distributed irregularly along the full rostrocaudal extent of the segments scanned with peaks concentrated in the ventral part of the lateral slices in all scans and subjects, consistent with the major channels of CSF flow. These results confirm that cardiac-induced changes are a significant source of noise likely to affect the detection of spinal Blood Oxygen Level Dependent (BOLD) responses. Most importantly, the complex spatiotemporal structure of cardiac noise is unlikely to be accounted for adequately by ad hoc linear methods, especially in data acquired using long TR (i.e. aliasing the cardiac frequency). However, the reliable spatiotemporal distribution of cardiac noise across scanning runs and within subjects may provide a valid means to identify and extract cardiac noise based on sICA methods.     

Visual estimation of the extent of myocardial hyperenhancement on late gadolinium-enhanced CMR in patients with hypertrophic cardiomyopathy

Aim

So far different approaches have been used to quantify late gadolinium enhancement (LGE) in patients with hypertrophic cardiomyopathy (HCM), but there is no general consensus on the gold standard, since histological data are scarce. The aim of our study was to investigate whether the determination of LGE in patients with HCM using a semiquantitative score based on the 17-segment model is feasible and has comparable accuracy to manual planimetry.

Methods

Forty-two patients with HCM underwent LGE cardiovascular magnetic resonance imaging. Determination of LGE by planimetry based on visual assessment was used as reference standard. Then the extent of LGE was assessed using a semiquantitative score based on the standard left ventricular 17-segment model. Each segment was scored for the distribution of LGE. The resulting summed score expressed as percentage of the maximum possible score was thereafter compared with the manual planimetric evaluation of LGE, expressed as a percentage of the left ventricular myocardial area.

Results

In 28 patients (66%), LGE was present. There was a good correlation between the semiquantitative score and the planimetric approach (r=0.89; y=0.819x+2.45; standard error of estimation=2.327; P<.0001). Additionally, the Bland–Altmann plot showed a high concordance between the two approaches (mean of the difference +1.7%). The inter- and intraobserver limits of agreement and the coefficients of repeatability based on measurements with the semiquantitative score of the extent of LGE were superior to planimetric measurements. Besides, the time requirement for the LGE determination using the semiquantitative score was found to be significantly reduced compared to manual planimetry (median 2 vs. 10 min).

Conclusions

Thus, a reliable global index of the size of the LGE is feasible and can easily be obtained from visual assessment with a semiquantitative score of the extent of the hyperenhancement.     

Advanced diffusion models in head and neck squamous cell carcinoma patients: Goodness of fit,relationships among diffusion parameters and comparison with dynamic contrast-enhanced perfusion

PurposeWe assessed advanced fitting models of diffusion weighted imaging (DWI) in head/neck squamous cell carcinoma (HNSCC) patients to determine the best goodness of fit and correlations among diffusion parameters. We compared these results with those of dynamic contrast-enhanced (DCE) perfusion parameters.Materials and methodsWe retrospectively evaluated 32 HNSCC patients (12 sinonasal, 20 pharynx/oral cavity). The DWI acquisition used single-shot spin-echo echo-planar imaging (EPI) with 12 b-values (0 − 2000). We calculated 14 DWI parameters using mono-exponential, bi-exponential, and tri-exponential models, stretched exponential model (SEM) and diffusion kurtosis imaging (DKI) models. We compared each model's goodness of fit using the residual sum of squares (RSS), Akaike Information Criterion (AIC) and Bayesian information criterion (BIC) value. We determined the correlation between each pair of DWI parameters and between each DWI parameter and DCE perfusion parameter.ResultsThe tri-exponential fit's RSS, AIC and BIC values were significantly smaller than those for bi-exponential fit. The RSS, AIC and BIC values of the SEM fit and DKI fit were significantly smaller than mono-exponential model. Significant correlations were observed in 30 pairs (sinonasal cavity) and 31 (sinonasal cavity group) among 91 DWI parameter combinations. Significant correlations were also observed in nine pairs (both sinonasal cavity and pharynx/oral cavity group) among 64 DWI/DCE perfusion parameter pairs, in particular, high positive correlations between the tri-exponential model's intermediate diffusion fraction (f₂) and the volume of the extracellular extravascular space per unit volume of tissue (v_e) were observed in both patient groups.ConclusionWe identified several correlations between DWI parameters by advanced fitting models and correlations between DWI and DCE parameters. These will help determine HNSCC patients' detailed tissue structures.     

Heavy ion induced charge exchange reactions: A preliminary study within the Constrained Molecular Dynamics model

We present a preliminary study of charge exchange heavy ion induced reactions based on the constrained molecular dynamics(CoMD) model.The purpose is to test the capability of the model in predicting the occurrence of single charge exchange(SCE) and double charge exchange(DCE) exit channels for three different entrance channels at the same laboratory incident energy.The nuclear reaction dynamics and nuclear interaction within the CoMD approach are the only ingredients that have given,at this stage,promising results for SCE and DCE cross section calculations.The obtained results suggest an upgrade and possible future employment of the model for studies relating to the production of exotic nuclei through charge exchange reactions or DCE reactions and their connection with neutrinoless double beta decay.     

Arterial spin labelling as a gadolinium-free alternative in the detection of prostate cancer

PurposeTo determine the capability of Gadolinium-free arterial spin labelling (ASL) sequences as novel, contrast-free, non-invasive alternative perfusion imaging method to differentiate prostate cancer (PCA) from benign prostate tissue compared to conventional DCE MRI.MethodsThirty men with histologically confirmed PCA were included in this prospectively enrolled single center cohort study. All patients received multiparametric MRI (T2, DWI, DCE) at 3 T with additional ASL of the PCA lesion. Primary endpoint was differentiability of PCA versus benign prostate tissue by signal intensities (SI) and contrast ratios (CR) in ASL in comparison to DCE. For DCE also Signal-Enhancement-Ratio (SER) of native and early contrast enhancement SI was assessed. Secondary objectives were differences regarding PCA localisation in peripheral (PZ) or transition zone (TZ) and PCA detection.ResultsIn both, ASL and DCE, average SI of PCA differed significantly from SI in benign tissue in the TZ and PZ (p < 0,01, respectively). ASL had significantly higher CR discerning PCA and benign tissue in PZ and TZ (PZ = 5.19; TZ = 6.45) compared to DCE SI (PZ = 1.61; TZ = 1.43) and DCE SER (PZ = 1.59; TZ = 1.43) (p < 0.01, respectively). In subjective evaluation, PCA could be detected in ASL in 28 patients, compared to 29 in DCE.ConclusionASL had significantly higher CR differentiating PCA from benign tissue in PZ and TZ compared to DCE. Visual detection of PCA does not differ significantly between the two sequences. As perfusion gadolinium-based contrast media is seen more critical in the last few years, ASL seems to be a promising alternative to DCE in PCA detection.     

Combined prostate diffusion tensor imaging and dynamic contrast enhanced MRI at 3T — quantitative correlation with biopsy

The purpose of this work was to compare diagnostic accuracy of Diffusion Tensor Imaging (DTI), dynamic contrast-enhanced magnetic resonance imaging (DCE MRI) and their combination in diagnosing prostate cancer. Twenty-five patients with clinical suspicion of prostate cancer underwent MRI, prior to transrectal ultrasound-guided biopsies. MRI data were correlated to biopsy results. Logistic regression models were constructed for the DTI parameters, DCE MRI parameters, and their combination. The areas under the receiver operator characteristic curves (AUC) were compared between the models. The nonparametric Wilcoxon signed rank test was used for statistical analysis. The sensitivity and specificity values were respectively 81% (74–87%) and 85% (79–90%) for DTI and 63% (55–70%) and 90% (85–94%) for DCE. The combination “DTI or DCE MRI” had 100% (97–100%) sensitivity and 77% (69–83%) specificity, while “DTI and DCE MRI” had 44% (37–52%) sensitivity and 98% (94–100%) specificity. The AUC for DTI+DCE parameters was significantly higher than that for either DTI (0.96 vs. 0.92, P=.0143) or DCE MRI parameters (0.96 vs. 0.87, P=.00187) alone. In conclusion, the combination of DTI and DCE MRI has significantly better accuracy in prostate cancer diagnosis than either technique alone.     

Assessment of Cardiorespiratory Interactions during Apneic Events in Sleep via Fuzzy Kernel Measures of Information Dynamics

Apnea and other breathing-related disorders have been linked to the development of hypertension or impairments of the cardiovascular, cognitive or metabolic systems. The combined assessment of multiple physiological signals acquired during sleep is of fundamental importance for providing additional insights about breathing disorder events and the associated impairments. In this work, we apply information-theoretic measures to describe the joint dynamics of cardiorespiratory physiological processes in a large group of patients reporting repeated episodes of hypopneas, apneas (central, obstructive, mixed) and respiratory effort related arousals (RERAs). We analyze the heart period as the target process and the airflow amplitude as the driver, computing the predictive information, the information storage, the information transfer, the internal information and the cross information, using a fuzzy kernel entropy estimator. The analyses were performed comparing the information measures among segments during, immediately before and after the respiratory event and with control segments. Results highlight a general tendency to decrease of predictive information and information storage of heart period, as well as of cross information and information transfer from respiration to heart period, during the breathing disordered events. The information-theoretic measures also vary according to the breathing disorder, and significant changes of information transfer can be detected during RERAs, suggesting that the latter could represent a risk factor for developing cardiovascular diseases. These findings reflect the impact of different sleep breathing disorders on respiratory sinus arrhythmia, suggesting overall higher complexity of the cardiac dynamics and weaker cardiorespiratory interactions which may have physiological and clinical relevance.     

Preliminary abnormal electrocardiogram segment screening method for Holter data based on long short-term memory networks

Holter usually monitors electrocardiogram(ECG)signals for more than 24 hours to capture short-lived cardiac abnormalities.In view of the large amount of Holter data and the fact that the normal part accounts for the majority,it is reasonable to design an algorithm that can automatically eliminate normal data segments as much as possible without missing any abnormal data segments,and then take the left segments to the doctors or the computer programs for further diagnosis.In this paper,we propose a preliminary abnormal segment screening method for Holter data.Based on long short-term memory(LSTM)networks,the prediction model is established and trained with the normal data of a monitored object.Then,on the basis of kernel density estimation,we learn the distribution law of prediction errors after applying the trained LSTM model to the regular data.Based on these,the preliminary abnormal ECG segment screening analysis is carried out without R wave detection.Experiments on the MIT-BIH arrhythmia database show that,under the condition of ensuring that no abnormal point is missed,53.89% of normal segments can be effectively obviated.This work can greatly reduce the workload of subsequent further processing.     

Region of interest and pixel-by-pixel analysis of dynamic contrast enhanced magnetic resonance imaging parameters and time-intensity curve shapes: a comparison in chondroid tumors

Dynamic contrast enhanced (DCE) MRI is widely acknowledged to be a helpful tool in the diagnosis and differentiation of tumors. In common clinical settings, the dynamic changes described by the time-intensity curves (TICs) are evaluated to find patterns of atypical tissue behavior, i.e., areas characterized by rapid contrast wash-in and wash-out. Despite the ease of this approach, there is no consensus about the specificity of the TIC shapes in discriminating tumor grades. We explore a new way of looking at TICs, where these are not averaged over a selected region of interest (ROI), but rendered pixel-by-pixel. In this way, the characteristic of the tissue is not given as a single TIC classification but as a distribution of the different TIC patterns. We applied this method in a group of patients with chondroid tumors and compared its outcome with the outcome of the standard ROI-based averaged TIC analysis. Furthermore, we focused on the problem of ROI selection in these tumors and how this affects the outcome of the TIC analysis. Finally, we investigated what relationship exists between the "standard" DCE-MRI parameter maximum enhancement (ME) and the TIC shape. CONCLUSIONS: We demonstrate that, where the ROI approach fails to show the presence of areas of rapid contrast wash-in and wash-out, the pixel-by-pixel approach reveals the coexistence of a heterogeneous pattern of TIC shapes. Secondly, we point out the differences in the DCE MRI parameters and tumor volume that can result when selecting the tumor based on DCE parameter maps or post-contrast T1-weighted images. Finally, we show that ME maps and TIC shape maps highlight different tissue areas and, therefore, the use of the ME maps is not appropriate for the correct identification of areas of atypical TICs.     

Magnetic resonance imaging in patients with unstable angina: comparison with acute myocardial infarction and normals

The role of magnetic resonance imaging in characterizing normal, ischemic and infarcted segments of myocardium was examined in 8 patients with unstable angina, 11 patients with acute myocardial infarction, and 7 patients with stable angina. Eleven normal volunteers were imaged for comparison. Myocardial segments in short axis magnetic resonance images were classified as normal or abnormal on the basis of perfusion changes observed in thallium-201 images in 22 patients and according to the electrocariographic localization of infarction in 4 patients. T2 relaxation time was measured in 57 myocardial segments with abnormal perfusion (24 with reversible and 33 with irreversible perfusion changes) and in 25 normally perfused segments. T2 measurements in normally perfused segments of patients with acute myocardial infarction, unstable angina and stable angina were within normal range derived from T2 measurements in 48 myocardial segments of 11 normal volunteers (42 +/- 10 ms). T2 in abnormal myocardial segments of patients with stable angina also was not significantly different from normal. T2 of abnormal segments in patients with unstable angina (64 +/- 14 in reversibly ischemic and 67 +/- 21 in the irreversibly ischemic segments) was prolonged when compared to normal (p less than 0.0001) and was not significantly different from T2 in abnormal segments of patients with acute myocardial infarction (62 +/- 18 for reversibly and 66 +/- 11 for irreversibly ischemic segments). The data indicate that T2 prolongation is not specific for acute myocardial infarction and may be observed in abnormally perfused segments of patients with unstable angina.(ABSTRACT TRUNCATED AT 250 WORDS)     

Dyskinesis in Chagasic myocardium: centerline analysis of wall motion using cardiac-gated magnetic resonance images of mice

We report on the use of centerline analysis of cardiac-gated magnetic resonance images to measure wall motion abnormalities in mice infected with Trypanosoma cruzi. To our knowledge, this is the first report of segmental wall motion abnormalities in an animal model of Chagas' disease. Chagas' disease patients with severe cardiac involvement exhibit mild hypokinesis in an extensive region of the left ventricle and dyskinesis in the apical region. We observed dyskinetic segments in a similar region of the hearts of infected wild-type mice. Dyskinesis was not observed in infected mice lacking macrophage inflammatory protein-1alpha, a chemokine that may play an important role in the cardiac remodeling that is normally observed in mouse models of Chagas' disease and in human patients. This study aimed to demonstrate the utility of cardiac-gated magnetic resonance imaging and centerline analysis as a straightforward method for monitoring regional left ventricular wall motion in transgenic and/or diseased mice.     

Acoustic effects of variation in vocal effort by men, women, and children

The acoustic effects of the adjustment in vocal effort that is required when the distance between speaker and addressee is varied over a large range (0.3-187.5 m) were investigated in phonated and, at shorter distances, also in whispered speech. Several characteristics were studied in the same sentence produced by men, women, and 7-year-old boys and girls: duration of vowels and consonants, pausing and occurrence of creaky voice, mean and range of F0, certain formant frequencies (F1 in [a] and F3), sound-pressure level (SPL) of voiced segments and [s], and spectral emphasis. In addition to levels and emphasis, vowel duration, F0, and F1 were substantially affected. "Vocal effort" was defined as the communication distance estimated by a group of listeners for each utterance. Most of the observed effects correlated better with this measure than with the actual distance, since some additional factors affected the speakers' choice. Differences between speaker groups emerged in segment durations, pausing behavior, and in the extent to which the SPL of [s] was affected. The whispered versions are compared with the phonated versions produced by the same speakers at the same distance. Several effects of whispering are found to be similar to those of increasing vocal effort.     

A feasible high spatiotemporal resolution breast DCE-MRI protocol for clinical settings

Three dimensional bilateral imaging is the standard for most clinical breast dynamic contrast-enhanced (DCE) MRI protocols. Because of high spatial resolution (sRes) requirement, the typical 1–2 min temporal resolution (tRes) afforded by a conventional full-k-space-sampling gradient echo (GRE) sequence precludes meaningful and accurate pharmacokinetic analysis of DCE time-course data. The commercially available, GRE-based, k-space undersampling and data sharing TWIST (time-resolved angiography with stochastic trajectories) sequence was used in this study to perform DCE-MRI exams on thirty one patients (with 36 suspicious breast lesions) before their biopsies. The TWIST DCE-MRI was immediately followed by a single-frame conventional GRE acquisition. Blinded from each other, three radiologist readers assessed agreements in multiple lesion morphology categories between the last set of TWIST DCE images and the conventional GRE images. Fleiss’ κ test was used to evaluate inter-reader agreement. The TWIST DCE time-course data were subjected to quantitative pharmacokinetic analyses. With a four-channel phased-array breast coil, the TWIST sequence produced DCE images with 20 s or less tRes and ~ 1.0×1.0×1.4 mm³ sRes. There were no significant differences in signal-to-noise (P=.45) and contrast-to-noise (P=.51) ratios between the TWIST and conventional GRE images. The agreements in morphology evaluations between the two image sets were excellent with the intra-reader agreement ranging from 79% for mass margin to 100% for mammographic density and the inter-reader κ value ranging from 0.54 (P<.0001) for lesion size to 1.00 (P<.0001) for background parenchymal enhancement. Quantitative analyses of the DCE time-course data provided higher breast cancer diagnostic accuracy (91% specificity at 100% sensitivity) than the current clinical practice of morphology and qualitative kinetics assessments. The TWIST sequence may be used in clinical settings to acquire high spatiotemporal resolution breast DCE-MRI images for both precise lesion morphology characterization and accurate pharmacokinetic analysis.     

Short-term forecasting of life-threatening cardiac arrhythmias based on symbolic dynamics and finite-time growth rates

Ventricular tachycardia or fibrillation (VT-VF) as fatal cardiac arrhythmias are the main factors triggering sudden cardiac death. The objective of this study is to find early signs of sustained VT-VF in patients with an implanted cardioverter-defibrillator (ICD). These devices are able to safeguard patients by returning their hearts to a normal rhythm via strong defibrillatory shocks; additionally, they store the 1000 beat-to-beat intervals immediately before the onset of a life-threatening arrhythmia. We study these 1000 beat-to-beat intervals of 17 chronic heart failure ICD patients before the onset of a life-threatening arrhythmia and at a control time, i.e., without a VT-VF event. To characterize these rather short data sets, we calculate heart rate variability parameters from the time and frequency domain, from symbolic dynamics as well as the finite-time growth rates. We find that neither the time nor the frequency domain parameters show significant differences between the VT-VF and the control time series. However, two parameters from symbolic dynamics as well as the finite-time growth rates discriminate significantly both groups. These findings could be of importance in algorithms for next generation ICD's to improve the diagnostics and therapy of VT-VF.     

Design and evaluation of an abbreviated pixelwise dynamic contrast enhancement analysis protocol for early extracellular volume fraction estimation

IntroductionT1-based method is considered as the gold standard for extracellular volume fraction (ECV) mapping. This technique requires at least a 10 min delay after injection to acquire the post injection T1 map. Quantitative analysis of Dynamic Contrast Enhancement (DCE) images could lead to an earlier estimation of an ECV like parameter (2 min). The purpose of this study was to design a quantitative pixel-wise DCE analysis workflow to assess the feasibility of an early estimation of ECV.MethodsFourteen patients with mitral valve prolapse were included in this study. The MR protocol, performed on a 3 T MR scanner, included MOLLI sequences for T1 maps acquisition and a standard SR-turboFlash sequence for dynamic acquisition. DCE data were acquired for at least 120 s. We implemented a full DCE analysis pipeline with a pre-processing step using an innovative motion correction algorithm (RC-REG algorithm) and a post-processing step using the extended Tofts Model (ECV_ETM). Estimated ECV_ETM maps were compared to standard T1-based ECV maps (ECV_T1) with both a Pearson correlation analysis and a group-wise analysis.ResultsImage and map quality assessment showed systematic improvements using the proposed workflow. Strong correlation was found between ECV_ETM, and ECV_T1 values (r-square = 0.87).ConclusionA DCE analysis workflow based on RC-REG algorithm and ETM analysis can provide good quality parametric maps. Therefore, it is possible to extract ECV values from a 2 min-long DCE acquisition that are strongly correlated with ECV values from the T1 based method.     

Classification of breast mass lesions using model-based analysis of the characteristic kinetic curve derived from fuzzy c-means clustering

The purpose of this study is to evaluate the diagnostic efficacy of the representative characteristic kinetic curve of dynamic contrast-enhanced (DCE) magnetic resonance imaging (MRI) extracted by fuzzy c-means (FCM) clustering for the discrimination of benign and malignant breast tumors using a novel computer-aided diagnosis (CAD) system. About the research data set, DCE-MRIs of 132 solid breast masses with definite histopathologic diagnosis (63 benign and 69 malignant) were used in this study. At first, the tumor region was automatically segmented using the region growing method based on the integrated color map formed by the combination of kinetic and area under curve color map. Then, the FCM clustering was used to identify the time-signal curve with the larger initial enhancement inside the segmented region as the representative kinetic curve, and then the parameters of the Tofts pharmacokinetic model for the representative kinetic curve were compared with conventional curve analysis (maximal enhancement, time to peak, uptake rate and washout rate) for each mass. The results were analyzed with a receiver operating characteristic curve and Student's t test to evaluate the classification performance. Accuracy, sensitivity, specificity, positive predictive value and negative predictive value of the combined model-based parameters of the extracted kinetic curve from FCM clustering were 86.36% (114/132), 85.51% (59/69), 87.30% (55/63), 88.06% (59/67) and 84.62% (55/65), better than those from a conventional curve analysis. The A(Z) value was 0.9154 for Tofts model-based parametric features, better than that for conventional curve analysis (0.8673), for discriminating malignant and benign lesions. In conclusion, model-based analysis of the characteristic kinetic curve of breast mass derived from FCM clustering provides effective lesion classification. This approach has potential in the development of a CAD system for DCE breast MRI.     

Continuity of the robustness of contextuality of empirical models

Recently, the robustness of contextuality (RoC) of an empirical model was discussed in [Sci. China-Phys. Mech. Astron. 59, 640303 (2016)], many important properties of the RoC have been proved except for its boundedness and continuity. The aim of this paper is to find an upper bound for the RoC over all of empirical models and prove that the RoC is a continuous function on the set of all empirical models. Lastly, a relationship between the RoC and the extent of violating the noncontextual inequalities is established for an n-cycle contextual box. This relationship implies that the RoC can be used to quantify the contextuality of n-cycle boxes.     

Magnetic resonance imaging dynamic contrast enhancement (DCE) characteristics of healed myocardial infarction differ from viable myocardium

Purpose

To determine whether healed myocardial infarction alters dynamic contrast-enhancement (DCE) curve shapes as well as late gadolinium-enhancement (LGE).

Materials and methods

Twenty patients with chronic myocardial infarction underwent MR imaging at 1.5 T with blood and myocardial T1 measurements before and after contrast administration for forty minutes. Viable and infarcted myocardial partition coefficients were calculated using multipoint slope methods for ten different DCE sampling intervals and windows. Partition coefficients and coefficients of determination were compared with paired statistical tests to assess the linearity of DCE curve shapes over the 40 min time period.

Results

Calculated partition coefficients did not vary significantly between methods (p = 0.325) for viable myocardium but did differ for infarcted myocardium (p < 0.001), indicating a difference in infarcted DCE. There was a significant difference between viable and infarcted myocardial partition coefficients estimates for all methods with the exception of methods that included measurements during the first 10 min after contrast agent administration.

Conclusion

Myocardial partition coefficients calculated from a slope calculation vary in healed myocardial infarction based on the selection of samples due to non-linear DCE curve shapes. Partition coefficient calculations are insensitive to data sampling effects in viable myocardium due to linear DCE curve shapes.     

MRI protocol optimization for quantitative DCE-MRI of the spine

PurposeIn this study we systematically investigated different Dynamic Contrast Enhancement (DCE)-MRI protocols in the spine, with the goal of finding an optimal protocol that provides data suitable for quantitative pharmacokinetic modelling (PKM).Materials and methodsIn 13 patients referred for MRI of the spine, DCE-MRI of the spine was performed with 2D and 3D MRI protocols on a 3T Philips Ingenuity MR system. A standard bolus of contrast agent (Dotarem - 0.2 ml/kg body weight) was injected intravenously at a speed of 3 ml/s. Different techniques for acceleration and motion compensation were tested: parallel imaging, partial-Fourier imaging and flow compensation. The quality of the DCE MRI images was scored on the basis of SNR, motion artefacts due to flow and respiration, signal enhancement, quality of the T₁ map and of the arterial input function, and quality of pharmacokinetic model fitting to the extended Tofts model.ResultsSagittal 3D sequences are to be preferred for PKM of the spine. Acceleration techniques were unsuccessful due to increased flow or motion artefacts. Motion compensating gradients failed to improve the DCE scans due to the longer echo time and the T₂* decay which becomes more dominant and leads to signal loss, especially in the aorta. The quality scoring revealed that the best method was a conventional 3D gradient–echo acquisition without any acceleration or motion compensation technique. The priority in the choice of sequence parameters should be given to reducing echo time and keeping the dynamic temporal resolution below 5 s. Increasing the number of acquisition, when possible, helps towards reducing flow artefacts. In our setting we achieved this with a sagittal 3D slab with 5 slices with a thickness of 4.5 mm and two acquisitions.ConclusionThe proposed DCE protocol, encompassing the spine and the descending aorta, produces a realistic arterial input function and dynamic data suitable for PKM.