Evaluation of current algorithms for segmentation of scar tissue from late gadolinium enhancement cardiovascular magnetic resonance of the left atrium: an open-access grand challenge.

BACKGROUND: Late Gadolinium enhancement (LGE) cardiovascular magnetic resonance (CMR) imaging can be used to visualise regions of fibrosis and scarring in the left atrium (LA) myocardium. This can be important for treatment stratification of patients with atrial fibrillation (AF) and for assessment of treatment after radio frequency catheter ablation (RFCA). In this paper we present a standardised evaluation benchmarking framework for algorithms segmenting fibrosis and scar from LGE CMR images. The algorithms reported are the response to an open challenge that was put to the medical imaging community through an ISBI (IEEE International Symposium on Biomedical Imaging) workshop. METHODS: The image database consisted of 60 multicenter, multivendor LGE CMR image datasets from patients with AF, with 30 images taken before and 30 after RFCA for the treatment of AF. A reference standard for scar and fibrosis was established by merging manual segmentations from three observers. Furthermore, scar was also quantified using 2, 3 and 4 standard deviations (SD) and full-width-at-half-maximum (FWHM) methods. Seven institutions responded to the challenge: Imperial College (IC), Mevis Fraunhofer (MV), Sunnybrook Health Sciences (SY), Harvard/Boston University (HB), Yale School of Medicine (YL), King's College London (KCL) and Utah CARMA (UTA, UTB). There were 8 different algorithms evaluated in this study. RESULTS: Some algorithms were able to perform significantly better than SD and FWHM methods in both pre- and post-ablation imaging. Segmentation in pre-ablation images was challenging and good correlation with the reference standard was found in post-ablation images. Overlap scores (out of 100) with the reference standard were as follows: Pre: IC = 37, MV = 22, SY = 17, YL = 48, KCL = 30, UTA = 42, UTB = 45; Post: IC = 76, MV = 85, SY = 73, HB = 76, YL = 84, KCL = 78, UTA = 78, UTB = 72. CONCLUSIONS: The study concludes that currently no algorithm is deemed clearly better than others. There is scope for further algorithmic developments in LA fibrosis and scar quantification from LGE CMR images. Benchmarking of future scar segmentation algorithms is thus important. The proposed benchmarking framework is made available as open-source and new participants can evaluate their algorithms via a web-based interface.

X-ray and magnetic resonance imaging fusion for cardiac resynchronization therapy.

Cardiac Resynchronization Therapy (CRT) can effectively treat left ventricle (LV) driven Heart Failure (HF). However, 30% of the CRT recipients do not experience symptomatic benefit. Recent studies show that the CRT response rate can reach 95% when the LV pacing lead is placed at an optimal site at a region of maximal LV dyssynchrony and away from myocardial scars. Cardiac Magnetic Resonance (CMR) can identify the optimal site in three dimensions (3D). 3D CMR data can be registered to clinical standard x-ray fluoroscopy to achieve an optimal pacing of the LV. We have developed a 3D CMR to 2D x-ray image registration method for CRT procedures. We have employed the LV pacing lead on x-ray images and coronary sinus on MR data as landmarks. The registration method makes use of a guidewire simulation algorithm, edge based image registration technique and x-ray C-arm tracking to register the coronary sinus and pacing lead landmarks.

Clinical testing of an optimized software solution for an automated, observer-independent evaluation of dopamine transporter SPECT studies.

UNLABELLED: A lack of standardized evaluation procedures for dopamine transporter (DAT) SPECT investigations impairs both intra- and interindividual comparisons as well as multicenter trials-for example, for assessment of disease progression or the response to various drug treatments. Therefore, the aim of this study was to evaluate a novel automated method, which has been specifically developed for a standardized quantification of N-(3-fluoropropyl)-2beta-carbomethoxy-3beta-(4-iodophenyl)nortropane (123I-FP-CIT) SPECT studies. METHODS: DAT binding ratios of 155 (123)I-FP-CIT SPECT studies in 14 control subjects and 141 patients referred to confirm or exclude a presynaptic dopaminergic deficit were determined manually and by a fully automated technique. The latter included coregistration of patient studies to an 123I-FP-CIT mean template of controls with specialized, nonrigid adjustment for variation in striatal location, followed by calculation of specific striatal DAT binding using a standardized 3-dimensional volume-of-interest (VOI) map. The map is based on a MR scan and covers the striatum (S), caudate (C), putamen (P), and an occipital reference region. The semiquantitative ratios of both methods were compared with the visual findings. RESULTS: Excellent linear correlations were observed between manually and automatically determined results (S: r = 0.99; C: r = 0.99; P: r = 0.99; P < 0.001, respectively). Automated evaluations delivered highly reproducible and visually exact coregistrations. Individual variations in striatal anatomy (e.g., atrophy) were considered and VOI positions were corrected before quantification. Both the manual and the automated method showed identical accuracy in supporting the visual diagnoses. CONCLUSION: In a large patient population, excellent agreement was observed between quantitative DAT results using a time-consuming, observer-dependent, conventional manual method and the objective, automated evaluation specifically developed for a standardized evaluation of 123I-FP-CIT SPECT studies. It is suggested that the novel automated technique may substantially facilitate both intra- and interindividual comparisons as well as multicenter trials.

Is iterative reconstruction an alternative to filtered backprojection in routine processing of dopamine transporter SPECT studies?

UNLABELLED: In general, striatal dopamine transporter (DAT) binding is assessed by use of data reconstructed by filtered backprojection (FBP). The aim of this study was to investigate whether the use of an iterative reconstruction algorithm (ordered-subset expectation maximization [OSEM]) may provide results comparable to or even better than those obtained by standard FBP. METHODS: In 50 patients with parkinsonian syndromes, SPECT scans were acquired 4 h after injection of 185 MBq of (123)I-fluoropropyl-2beta-carbomethoxy-3beta-(4-iodophenyl)tropane ((123)I-FP-CIT) by use of a triple-head gamma-camera fitted with low-energy, high-resolution fanbeam collimators. After reconstruction by FBP and OSEM, data were filtered with a Butterworth filter and corrected for attenuation. Patient studies were automatically fitted to a mean template with a corresponding 3-dimensional (3D) volume-of-interest map covering the striatum, caudate, and putamen as well as an occipital reference region to calculate specific DAT binding. In addition, studies with an anthropomorphic 3D striatal phantom were performed to mimic different pathologies. RESULTS: Visual assessment of phantom and patient data suggested a better separation between the caudate and the putamen in studies reconstructed by OSEM than in those reconstructed by FBP. There was an excellent correlation between specific DAT binding assessed by OSEM and that assessed by FBP (R(2) values: striatum, 0.999; caudate, 0.998; putamen, 0.998). Mean specific striatal binding obtained by OSEM was approximately 6% lower than that obtained by FBP. In no case was diagnostic information from OSEM inferior to that from FBP. CONCLUSION: Iterative reconstruction of (123)I-FP-CIT SPECT studies for the assessment of DAT is feasible in routine clinical practice. A close correlation between FBP and OSEM data suggested that the latter also allow reliable quantification of DAT binding. Because of a better separation between the caudate and the putamen in the visual evaluation, as suggested by phantom and patient studies, OSEM may even be considered the preferable approach.

Diagnostic performance of a 3-D automated quantification method of dopamine D2 receptor SPECT studies in the differential diagnosis of parkinsonism.

BACKGROUND: Assessment of post-synaptic D2 receptors with 123I-IBZM SPECT is helpful in distinguishing idiopathic (IPS) from other parkinsonian syndromes (non-IPS). AIM: To evaluate the diagnostic performance of a recently introduced three-dimensional automated quantification method in a large group of parkinsonian patients. METHODS: IBZM SPECT was performed in 101 consecutive patients with IPS (n = 49) and non-IPS (n = 52). Striatal/frontal cortex binding ratios were assessed by a standard manual quantification method and by the automated method. For the latter patient studies were registered to a mean template of healthy controls (n = 13). IBZM binding was calculated from a 3-D volume-of-interest map established on the normal template. The diagnostic performance of the automated and manual approaches were assessed by receiver operating characteristic (ROC) analyses. RESULTS: Specific striatal binding ratios of both quantification methods showed a close linear relationship (y = 0.81x + 0.1188; R2 = 0.8062). At optimal decision thresholds sensitivity and specificity were 87% and 90% for the automated, and 85% and 90% for the manual method, respectively. The area under the ROC curve was 0.92 for the automated and 0.93 for the manual method, showing no statistical difference. The area under the ROC curve corresponding to a false positive fraction from 0% to 20% was 0.163 for the automated and 0.166 for the manual evaluation. CONCLUSIONS: The diagnostic performance of an automated 3-D quantification method for IBZM SPECT studies has been shown to be equal to, or even better than, a standard manual technique. Advantages of automated quantifications are observer independence and fast processing times. This method may be also used as a platform for processing large data sets/multicentre studies in order to objectively evaluate basal ganglia disorders.

Multiscale properties of weighted total variation flow with applications to denoising and registration.

Images consist of structures of varying scales: large scale structures such as flat regions, and small scale structures such as noise, textures, and rapidly oscillatory patterns. In the hierarchical (BV, L(2)) image decomposition, Tadmor, et al. (2004) start with extracting coarse scale structures from a given image, and successively extract finer structures from the residuals in each step of the iterative decomposition. We propose to begin instead by extracting the finest structures from the given image and then proceed to extract increasingly coarser structures. In most images, noise could be considered as a fine scale structure. Thus, starting the image decomposition with finer scales, rather than large scales, leads to fast denoising. We note that our approach turns out to be equivalent to the nonstationary regularization in Scherzer and Weickert (2000). The continuous limit of this procedure leads to a time-scaled version of total variation flow. Motivated by specific clinical applications, we introduce an image depending weight in the regularization functional, and study the corresponding weighted TV flow. We show that the edge-preserving property of the multiscale representation of an input image obtained with the weighted TV flow can be enhanced and localized by appropriate choice of the weight. We use this in developing an efficient and edge-preserving denoising algorithm with control on speed and localization properties. We examine analytical properties of the weighted TV flow that give precise information about the denoising speed and the rate of change of energy of the images. An additional contribution of the paper is to use the images obtained at different scales for robust multiscale registration. We show that the inherently multiscale nature of the weighted TV flow improved performance for registration of noisy cardiac MRI images, compared to other methods such as bilateral or Gaussian filtering. A clinical application of the multiscale registration algorithm is also demonstrated for aligning viability assessment magnetic resonance (MR) images from 8 patients with previous myocardial infarctions.

Loss of dopamine transporter binding in Parkinson's disease follows a single exponential rather than linear decline.

UNLABELLED: Imaging of L-dopa uptake or dopamine transporter binding can monitor the progression of Parkinson's disease. Most follow-up studies have provided data best fitted by a linear decline of their outcome measure. However, in these studies, patients were repeatedly scanned during their first years after a diagnosis had been established. METHODS: We followed 6 patients with early Parkinson's disease for 7.5 y using 123I-labeled N-(3-iodopropene-2-yl)-2beta-carbomethoxy-3beta-(4-chlorophenyl) tropane and SPECT. RESULTS: Loss of dopamine transporter binding was best fitted using a single exponential approximation. A 63% loss (tau [time constant tau]) was calculated as 5.18 +/- 7.62 y in the putamen and 10.62 +/- 31.4 y in the caudate nucleus when a 3-parameter fit was used. CONCLUSION: These data approximate, for what is to our knowledge the first time, the decline of dopamine transporter binding as expected in biologic systems and may allow for models that correct for exponential decline to be developed and for disease-modifying effects in patients with advanced disease to be determined.

Automatic functional analysis of left ventricle in cardiac cine MRI.

RATIONALE AND OBJECTIVES: A fully automated left ventricle segmentation method for the functional analysis of cine short axis (SAX) magnetic resonance (MR) images was developed, and its performance evaluated with 133 studies of subjects with diverse pathology: ischemic heart failure (n=34), non-ischemic heart failure (n=30), hypertrophy (n=32), and healthy (n=37). MATERIALS AND METHODS: The proposed automatic method locates the left ventricle (LV), then for each image detects the contours of the endocardium, epicardium, papillary muscles and trabeculations. Manually and automatically determined contours and functional parameters were compared quantitatively. RESULTS: There was no significant difference between automatically and manually determined end systolic volume (ESV), end diastolic volume (EDV), ejection fraction (EF) and left ventricular mass (LVM) for each of the four groups (paired sample t-test, α=0.05). The automatically determined functional parameters showed high correlations with those derived from manual contours, and the Bland-Altman analysis biases were small (1.51 mL, 1.69 mL, -0.02%, -0.66 g for ESV, EDV, EF and LVM, respectively). CONCLUSIONS: The proposed technique automatically and rapidly detects endocardial, epicardial, papillary muscles' and trabeculations' contours providing accurate and reproducible quantitative MRI parameters, including LV mass and EF.

Automated quantification of myocardial infarction using graph cuts on contrast delayed enhanced magnetic resonance images.

In this work, we propose a semi-automated myocardial infarction quantification method for cardiac contrast delayed enhancement magnetic resonance images (DE-MRI). Advantages of this method include that it reduces manual contouring of the left ventricle, obviates a remote myocardium region, and automatically distinguishes infarct, healthy and heterogeneous ("gray zone") tissue despite variability in intensity and noise across images. Quantitative evaluation results showed that the automatically determined infarct core and gray zone size have high correlation with that derived from the averaged results of the manual full width at half maximum (FWHM) methods (R(2)=0.99 for infarct core and gray zone size). Compared with the manual method, a much better reproducibility was achieved with the proposed algorithm and it shortens the evaluation time to one second per image, compared with 2-5 min per image for the manual method.

Pattern recognition of abnormal left ventricle wall motion in cardiac MR.

There are four main problems that limit application of pattern recognition techniques for recognition of abnormal cardiac left ventricle (LV) wall motion: (1) Normalization of the LV's size, shape, intensity level and position; (2) defining a spatial correspondence between phases and subjects; (3) extracting features; (4) and discriminating abnormal from normal wall motion. Solving these four problems is required for application of pattern recognition techniques to classify the normal and abnormal LV wall motion. In this work, we introduce a normalization scheme to solve the first and second problems. With this scheme, LVs are normalized to the same position, size, and intensity level. Using the normalized images, we proposed an intra-segment classification criterion based on a correlation measure to solve the third and fourth problems. Application of the method to recognition of abnormal cardiac MR LV wall motion showed promising results.

Innovations in imaging for chronic total occlusions: a glimpse into the future of angiography's blind-spot.

Chronic total occlusions (CTOs) are a subset of lesions that present a considerable burden to cardiovascular patients. There exists a strong clinical desire to improve non-surgical options for CTO revascularization. While several techniques, devices, and guide wires have been developed and refined for use in CTOs, the inability of angiography to adequately visualize occluded arterial segments makes interventions in this setting technically challenging. This review describes the current status of several invasive and non-invasive imaging techniques that may facilitate improved image guidance during CTO revascularization, with the goals of improving procedure safety and efficacy while reducing the time required to complete these interventions. Cardiac imaging also has important potential roles in selecting patients most likely to benefit from revascularization as well as pre-procedural planning, post-procedural assessment of revascularized segments and long-term outcomes studies. Modalities discussed include non-invasive techniques, such as CT(computed tomography) angiography and cardiac magnetic resonance imaging (MRI), as well as invasive techniques, such as intravascular ultrasound, optical coherence tomography, intravascular MRI, and conventional angiography. While some of these techniques have some evidence to support their use at present, others are at earlier stages of development. Strategies that combine imaging techniques with the use of interventional therapies may provide significant opportunities to improve results in CTO interventions and represent an active area of investigation.

Does combined imaging of the pre- and postsynaptic dopaminergic system increase the diagnostic accuracy in the differential diagnosis of parkinsonism?

PURPOSE: We hypothesized that combining pre- and postsynaptic quantitative information about the dopaminergic system would provide a higher diagnostic accuracy in the differential diagnosis of parkinsonism than specific striatal D(2) receptor binding alone. Therefore, the aim of the study was to introduce new semi-quantitative parameters and evaluate their ability to discriminate between Parkinson's disease (IPS) and non-idiopathic parkinsonian syndromes (non-IPS). METHODS: In 100 patients (69 IPS, 31 non-IPS), postsynaptic [(123)I]IBZM and presynaptic [(123)I]FP-CIT SPECT scans were evaluated by observer-independent techniques. The diagnostic performances of striatal dopamine transporter (DAT) and D(2) receptor binding, their respective asymmetries, and a combination of pre- and postsynaptic asymmetry were evaluated with ROC analyses. A logistic regression model was generated combining factors to calculate the probability for each patient of belonging to either diagnostic group. RESULTS: D(2) receptor binding provided a sensitivity of 87.1% and a specificity of 72.5% with an area under the curve (AUC) of 0.866. The AUCs of other single parameters were lower than that of D(2) binding. A gain of diagnostic power (p = 0.026) was reached with a model combining pre- and postsynaptic asymmetries and D(2) binding (sensitivity 90.3%, specificity 73.9%, AUC 0.893). CONCLUSION: The combination of quantitative parameters of presynaptic DAT and postsynaptic D(2) receptor binding demonstrates superior diagnostic power in the differentiation of patients with IPS and non-IPS than the established approach based on D(2) binding alone. Striatal D(2) receptor binding and the combination of DAT and IBZM binding asymmetries are the factors contributing most in separating these diagnostic groups.

Cross-camera comparison of SPECT measurements of a 3-D anthropomorphic basal ganglia phantom.

PURPOSE: SPECT examinations of neurotransmitter systems in the brain have to be comparable between centres to generate a comprehensive data pool, e.g. for multicentre studies. Equipment-specific effects on quantitative evaluations and corresponding methods for compensation, however, have been insufficiently examined. Previous studies have shown that quantitative results may vary significantly according to the imaging equipment used, thereby affecting clinical interpretation of the data. The aim of this study was to determine correction factors for common camera/collimator combinations based on standardised measurements of an anthropomorphic 3D basal ganglia phantom to compensate for the effects of different SPECT camera/collimator equipment. The latter may serve as a model for human studies of the dopaminergic system. METHODS: The striatum and background chambers of a commercially available phantom (RSD Alderson) were filled with various( 123)I concentrations encompassing specific striatum/background ratios from 0.6 to 16.1. This setup was imaged with the following four camera/collimator combinations: Siemens Multispect 3 fitted with LEHR and( 123)I parallel-hole collimators, Siemens ECAM with LEHR parallel-hole collimators and Philips Prism 3,000 fitted with LEHR fanbeam collimators, using standardised protocols for acquisition and reconstruction. All scans were automatically co-registered to a SPECT template of the phantom and quantified using a 3D volume of interest (VOI) map based on a CT scan of the phantom. All striatal/background ratios calculated by SPECT were compared with the true ratios calculated from the measurements in a well counter. Regression analyses were performed and recovery correction factors between measured and true ratios determined. RESULTS: The relation between true and measured ratios could be sufficiently described by a linear regression for each camera/collimator combination without relevant improvement when using second-order polynomial regression models. The recovery correction factors and standard errors were 2.04+/-0.04 for the Philips Prism 3,000, 2.67+/-0.03 for the Siemens Multispect 3/LEHR parallel-hole collimators, 2.15+/-0.03 for the Siemens Multispect 3/(123)I collimators and 2.81+/-0.03 for the Siemens ECAM. Percentage recovery ranged from 36% to 49%. CONCLUSION: Measurements of a 3D basal ganglia phantom with various imaging devices revealed linear correlations between measured and true striatal/background ratios. Based on these findings, adjustment of quantitative results between different equipment seems possible, provided that acquisition, reconstruction and evaluation are adequately standardised. The use of identical evaluation methods in phantom and patient studies (comparable shape, size and location of the VOIs) might allow transfer of the calculated correction factors from phantom to studies of the dopaminergic system in patients.