[Show abstract][Hide abstract] ABSTRACT: To determine whether intrathoracic fat volumes are associated with presence and chronicity of atrial fibrillation (AF) and radiofrequency ablation (RFA) treatment outcome.
IRB approval was obtained and patient consent was waived for this HIPAA-compliant retrospective study. 169 patients with AF (75 non-paroxysmal and 94 paroxysmal) and 62 control patients underwent cardiac CT examination. Extrapericardial (EPFV) and epicardial fat volumes (EFV) were measured on CT, the sum of which is the total intrathoracic fat volume. Associations between these three fat volumes and presence and chronicity of AF, and outcome after RFA, were evaluated using logistic regression analysis.
EFV was significantly associated with presence [OR 1.01 (95 % CI 1.003-1.03), p = 0.01], chronicity of AF [1.008 (1.001-1.020), p = 0.03] and AF recurrence after RFA [1.009 (1.001-1.01), p = 0.02] after adjustment for age, gender and BMI. Patients with a larger EFV had a shorter time to AF recurrence (p = 0.017) and a higher rate of recurrence (54 % vs 46 %) (p = 0.002) after RFA. EPFV had no significant associations.
Increased epicardial fat is associated with the presence and chronicity of AF, a higher probability of AF recurrence after RFA and a shorter AF-free interval.
• Increased epicardial fat is associated with presence and chronicity of atrial fibrillation • Extensive epicardial fat is associated with earlier recurrences of AF after ablation • Extensive epicardial fat may reduce transmurality of ablation by affecting current dynamics.
European Radiology 03/2015; 25(8). DOI:10.1007/s00330-015-3643-1 · 4.01 Impact Factor
[Show abstract][Hide abstract] ABSTRACT: Purpose:
The authors are developing a computer-aided detection system to assist radiologists in analysis of coronary artery disease in coronary CT angiograms (cCTA). This study evaluated the accuracy of the authors' coronary artery segmentation and tracking method which are the essential steps to define the search space for the detection of atherosclerotic plaques.
The heart region in cCTA is segmented and the vascular structures are enhanced using the authors' multiscale coronary artery response (MSCAR) method that performed 3D multiscale filtering and analysis of the eigenvalues of Hessian matrices. Starting from seed points at the origins of the left and right coronary arteries, a 3D rolling balloon region growing (RBG) method that adapts to the local vessel size segmented and tracked each of the coronary arteries and identifies the branches along the tracked vessels. The branches are queued and subsequently tracked until the queue is exhausted. With Institutional Review Board approval, 62 cCTA were collected retrospectively from the authors' patient files. Three experienced cardiothoracic radiologists manually tracked and marked center points of the coronary arteries as reference standard following the 17-segment model that includes clinically significant coronary arteries. Two radiologists visually examined the computer-segmented vessels and marked the mistakenly tracked veins and noisy structures as false positives (FPs). For the 62 cases, the radiologists marked a total of 10191 center points on 865 visible coronary artery segments.
The computer-segmented vessels overlapped with 83.6% (8520/10191) of the center points. Relative to the 865 radiologist-marked segments, the sensitivity reached 91.9% (795/865) if a true positive is defined as a computer-segmented vessel that overlapped with at least 10% of the reference center points marked on the segment. When the overlap threshold is increased to 50% and 100%, the sensitivities were 86.2% and 53.4%, respectively. For the 62 test cases, a total of 55 FPs were identified by radiologist in 23 of the cases.
The authors' MSCAR-RBG method achieved high sensitivity for coronary artery segmentation and tracking. Studies are underway to further improve the accuracy for the arterial segments affected by motion artifacts, severe calcified and noncalcified soft plaques, and to reduce the false tracking of the veins and other noisy structures. Methods are also being developed to detect coronary artery disease along the tracked vessels.
Medical Physics 08/2014; 41(8):081912. DOI:10.1118/1.4890294 · 2.64 Impact Factor
[Show abstract][Hide abstract] ABSTRACT: Purpose:
The buildup of noncalcified plaques (NCPs) that are vulnerable to rupture in coronary arteries is a risk for myocardial infarction. Interpretation of coronary CT angiography (cCTA) to search for NCP is a challenging task for radiologists due to the low CT number of NCP, the large number of coronary arteries, and multiple phase CT acquisition. The authors conducted a preliminary study to develop machine learning method for automated detection of NCPs in cCTA.
With IRB approval, a data set of 83 ECG-gated contrast enhanced cCTA scans with 120 NCPs was collected retrospectively from patient files. A multiscale coronary artery response and rolling balloon region growing (MSCAR-RBG) method was applied to each cCTA volume to extract the coronary arterial trees. Each extracted vessel was reformatted to a straightened volume composed of cCTA slices perpendicular to the vessel centerline. A topological soft-gradient (TSG) detection method was developed to prescreen for NCP candidates by analyzing the 2D topological features of the radial gradient field surface along the vessel wall. The NCP candidates were then characterized by a luminal analysis that used 3D geometric features to quantify the shape information and gray-level features to evaluate the density of the NCP candidates. With machine learning techniques, useful features were identified and combined into an NCP score to differentiate true NCPs from false positives (FPs). To evaluate the effectiveness of the image analysis methods, the authors performed tenfold cross-validation with the available data set. Receiver operating characteristic (ROC) analysis was used to assess the classification performance of individual features and the NCP score. The overall detection performance was estimated by free response ROC (FROC) analysis.
With our TSG prescreening method, a prescreening sensitivity of 92.5% (111/120) was achieved with a total of 1181 FPs (14.2 FPs/scan). On average, six features were selected during the tenfold cross-validation training. The average area under the ROC curve (AUC) value for training was 0.87 ± 0.01 and the AUC value for validation was 0.85 ± 0.01. Using the NCP score, FROC analysis of the validation set showed that the FP rates were reduced to 3.16, 1.90, and 1.39 FPs/scan at sensitivities of 90%, 80%, and 70%, respectively.
The topological soft-gradient prescreening method in combination with the luminal analysis for FP reduction was effective for detection of NCPs in cCTA, including NCPs causing positive or negative vessel remodeling. The accuracy of vessel segmentation, tracking, and centerline identification has a strong impact on NCP detection. Studies are underway to further improve these techniques and reduce the FPs of the CADe system.
Medical Physics 08/2014; 41(8):081901. DOI:10.1118/1.4885958 · 2.64 Impact Factor
[Show abstract][Hide abstract] ABSTRACT: IntroductionLeft ventricular (LV) and right ventricular (RV) volumetric and functional parameters are important biomarkers for morbidity and mortality in patients with heart failure.PurposeTo retrospectively determine reference mean values of LV and RV volume, function and mass normalised by age, gender and body surface area (BSA) from retrospectively electrocardiographically gated 64-slice cardiac computed tomography (CCT) by using automated analysis software in healthy adults.Materials and Methods
The study was approved by the institutional review board with a waiver of informed consent. Seventy-four healthy subjects (49% female, mean age 49.6 ± 11) free of hypertension and hypercholesterolaemia with a normal CCT formed the study population. Analyses of LV and RV volume (end-diastolic, end-systolic and stroke volumes), function (ejection fraction), LV mass and inter-rater reproducibility were performed with commercially available analysis software capable of automated contour detection. General linear model analysis was performed to assess statistical significance by age group after adjustment for gender and BSA. Bland–Altman analysis assessed the inter-rater agreement.ResultsThe reference range for LV and RV volume, function, and LV mass was normalised to age, gender and BSA. Statistically significant differences were noted between genders in both LV mass and RV volume (P-value < 0.0001). Age, in concert with gender, was associated with significant differences in RV end-diastolic volume and LV ejection fraction (P-values 0.027 and 0.03). Bland–Altman analysis showed acceptable limits of agreement (±1.5% for ejection fraction) without systematic error.ConclusionLV and RV volume, function and mass normalised to age, gender and BSA can be reported from CCT datasets, providing additional information important for patient management.
Journal of Medical Imaging and Radiation Oncology 06/2014; 58(5). DOI:10.1111/1754-9485.12186 · 1.11 Impact Factor
[Show abstract][Hide abstract] ABSTRACT: Non-calcified plaque (NCP) detection in coronary CT angiography (cCTA) is challenging due to the low CT number of NCP, the large number of coronary arteries and multiple phase CT acquisition. We are developing computer-vision methods for automated detection of NCPs in cCTA. A data set of 62 cCTA scans with 87 NCPs was collected retrospectively from patient files. Multiscale coronary vessel enhancement and rolling balloon tracking were first applied to each cCTA volume to extract the coronary artery trees. Each extracted vessel was reformatted to a straightened volume composed of cCTA slices perpendicular to the vessel centerline. A topological soft-gradient (TSG) detection method was developed to prescreen for both positive and negative remodeling candidates by analyzing the 2D topological features of the radial gradient field surface along the vessel wall. A quantitative luminal analysis was newly designed for feature extraction and false positive (FP) reduction. We extracted 9 geometric features and 6 gray-level features, to quantify the differences between NCPs and FPs. The gray-level features included 4 features to measure local statistical characteristics and 2 asymmetry features to measure the asymmetric spatial location of gray-level density along the vessel centerline. The geometric features included a radius differential feature and 8 features extracted from two transformed volumes: the volumetric shape indexing and the gradient direction mapping volumes. With a machine learning algorithm and feature selection method, useful features were selected and combined into an NCP likelihood measure to differentiate TPs from FPs. With the NCP likelihood measure as a decision variable in the receiver operating characteristic (ROC) analysis, the area under the curve achieved a value of 0.85±0.01, indicating that the luminal analysis is effective in reducing FPs for NCP detection.
[Show abstract][Hide abstract] ABSTRACT: Sudden cardiac death is defined as death from unexpected circulatory arrest-usually a result of cardiac arrhythmia-that occurs within 1 hour of the onset of symptoms. Proper and timely identification of individuals at risk for sudden cardiac death and the diagnosis of its predisposing conditions are vital. A careful history and physical examination, in addition to electrocardiography and cardiac imaging, are essential to identify conditions associated with sudden cardiac death. Among young adults (18-35 years), sudden cardiac death most commonly results from a previously undiagnosed congenital or hereditary condition, such as coronary artery anomalies and inherited cardiomyopathies (eg, hypertrophic cardiomyopathy, arrhythmogenic right ventricular cardiomyopathy [ARVC], dilated cardiomyopathy, and noncompaction cardiomyopathy). Overall, the most common causes of sudden cardiac death in young adults are, in descending order of frequency, hypertrophic cardiomyopathy, coronary artery anomalies with an interarterial or intramural course, and ARVC. Often, sudden cardiac death is precipitated by ventricular tachycardia or fibrillation and may be prevented with an implantable cardioverter defibrillator (ICD). Risk stratification to determine the need for an ICD is challenging and involves imaging, particularly echocardiography and cardiac magnetic resonance (MR) imaging. Coronary artery anomalies, a diverse group of congenital disorders with a variable manifestation, may be depicted at coronary computed tomographic angiography or MR angiography. A thorough understanding of clinical risk stratification, imaging features, and complementary diagnostic tools for the evaluation of cardiac disorders that may lead to sudden cardiac death is essential to effectively use imaging to guide diagnosis and therapy.
[Show abstract][Hide abstract] ABSTRACT: A 3D multiscale intensity homogeneity transformation (MIHT) method was
developed to reduce false positives (FPs) in our previously developed
CAD system for pulmonary embolism (PE) detection. In MIHT, the voxel
intensity of a PE candidate region was transformed to an intensity
homogeneity value (IHV) with respect to the local median intensity. The
IHVs were calculated in multiscales (MIHVs) to measure the intensity
homogeneity, taking into account vessels of different sizes and
different degrees of occlusion. Seven new features including the
entropy, gradient, and moments that characterized the intensity
distributions of the candidate regions were derived from the MIHVs and
combined with the previously designed features that described the shape
and intensity of PE candidates for the training of a linear classifier
to reduce the FPs. 59 CTPA PE cases were collected from our patient
files (UM set) with IRB approval and 69 cases from the PIOPED II data
set with access permission. 595 and 800 PEs were identified as reference
standard by experienced thoracic radiologists in the UM and PIOPED set,
respectively. FROC analysis was used for performance evaluation.
Compared with our previous CAD system, at a test sensitivity of 80%, the
new method reduced the FP rate from 18.9 to 14.1/scan for the PIOPED set
when the classifier was trained with the UM set and from 22.6 to
16.0/scan vice versa. The improvement was statistically significant
(p<0.05) by JAFROC analysis. This study demonstrated that the MIHT
method is effective in reducing FPs and improving the performance of the
Proceedings of SPIE - The International Society for Optical Engineering 04/2013; DOI:10.1117/12.2008053 · 0.20 Impact Factor
[Show abstract][Hide abstract] ABSTRACT: We are developing an automated registration method for coronary arterial
trees from multiple-phase cCTA to build a best-quality tree to
facilitate detection of stenotic plaques. Cubic B-spline with fast
localized optimization (CBSO) is designed to register the initially
segmented left and right coronary arterial trees (LCA or RCA) separately
in adjacent phase pairs where displacements are small. First, the
corresponding trees in phase 1 and 2 are registered. The phase 3 tree is
then registered to the combined tree. Similarly the trees in phases 4,
5, and 6 are registered. An affine transform with quadratic terms and
nonlinear simplex optimization (AQSO) is designed to register the trees
between phases with large displacements, namely, registering the
combined tree from phases 1, 2, and 3 to that from phases 4, 5, and 6.
Finally, CBSO is again applied to the AQSO registered volumes for final
refinement. The costs determined by the distances between the vessel
centerlines, bifurcation points and voxels of the trees are minimized to
guide both CBSO and AQSO registration. The registration performance was
evaluated on 22 LCA and 22 RCA trees on 22 CTA scans with 6 phases from
22 patients. The average distance between the centerlines of the
registered trees was used as a registration quality index. The average
distances for LCA and RCA registration for 6 phases and 22 patients were
1.49 and 1.43 pixels, respectively. This study demonstrates the
feasibility of using automated method for registration of coronary
arterial trees from multiple cCTA phases.
Proceedings of SPIE - The International Society for Optical Engineering 03/2013; 59(16). DOI:10.1117/12.2008058 · 0.20 Impact Factor
[Show abstract][Hide abstract] ABSTRACT: The curved planar reformation (CPR) method re-samples the vascular
structures along the vessel centerline to generate longitudinal
cross-section views. The CPR technique has been commonly used in
coronary CTA workstation to facilitate radiologists' visual assessment
of coronary diseases, but has not yet been used for pulmonary vessel
analysis in CTPA due to the complicated tree structures and the vast
network of pulmonary vasculature. In this study, a new curved planar
reformation and optimal path tracing (CROP) method was developed to
facilitate feature extraction and false positive (FP) reduction and
improve our PE detection system. PE candidates are first identified in
the segmented pulmonary vessels at prescreening. Based on Dijkstra's
algorithm, the optimal path (OP) is traced from the pulmonary trunk
bifurcation point to each PE candidate. The traced vessel is then
straightened and a reformatted volume is generated using CPR. Eleven new
features that characterize the intensity, gradient, and topology are
extracted from the PE candidate in the CPR volume and combined with the
previously developed 9 features to form a new feature space for FP
classification. With IRB approval, CTPA of 59 PE cases were
retrospectively collected from our patient files (UM set) and 69 PE
cases from the PIOPED II data set with access permission. 595 and 800
PEs were manually marked by experienced radiologists as reference
standard for the UM and PIOPED set, respectively. At a test sensitivity
of 80%, the average FP rate was improved from 18.9 to 11.9 FPs/case with
the new method for the PIOPED set when the UM set was used for training.
The FP rate was improved from 22.6 to 14.2 FPs/case for the UM set when
the PIOPED set was used for training. The improvement in the free
response receiver operating characteristic (FROC) curves was
statistically significant (p<0.05) by JAFROC analysis, indicating
that the new features extracted from the CROP method are useful for FP
Proceedings of SPIE - The International Society for Optical Engineering 03/2013; 8670:35-. DOI:10.1117/12.2008048 · 0.20 Impact Factor
[Show abstract][Hide abstract] ABSTRACT: Non-calcified plaque (NCP) detection in coronary CT angiography (cCTA)
is challenging due to the low CT number of NCP, the large number of
coronary arteries and multiple phase CT acquisition. We are developing
computervision methods for automated detection of NCPs in cCTA. A data
set of 62 cCTA scans with 87 NCPs was collected retrospectively from
patient files. Multiscale coronary vessel enhancement and rolling
balloon tracking were first applied to each cCTA volume to extract the
coronary artery trees. Each extracted vessel was reformatted to a
straightened volume composed of cCTA slices perpendicular to the vessel
centerline. A new topological soft-gradient (TSG) detection method was
developed to prescreen for both positive and negative remodeling
candidates by analyzing the 2D topological features of the radial
gradient field surface along the vessel wall. Nineteen features were
designed to describe the relative location along the coronary artery,
shape, distribution of CT values, and radial gradients of each NCP
candidate. With a machine learning algorithm and a two-loop
leave-one-case-out training and testing resampling method, useful
features were selected and combined into an NCP likelihood measure to
differentiate TPs from FPs. The detection performance was evaluated by
FROC analysis. Our TSG method achieved a sensitivity of 96.6% with 35.4
FPs/scan at prescreening. Classification with the NCP likelihood measure
reduced the FP rates to 13.1, 10.0 and 6.7 FPs/scan at sensitivities of
90%, 80%, and 70%, respectively. These results demonstrated that the new
TSG method is useful for computerized detection of NCPs in cCTA.
Proceedings of SPIE - The International Society for Optical Engineering 03/2013; DOI:10.1117/12.2008047 · 0.20 Impact Factor
[Show abstract][Hide abstract] ABSTRACT: PURPOSE
We conducted a preliminary study to develop machine learning methods for automated detection of non-calcified plaques (NCPs) in coronary CTA (cCTA).
METHOD AND MATERIALS
With IRB approval, a data set of 38 cCTA scans was retrospectively collected from 38 patient files. Experienced cardiothoracic radiologists marked the location of NCPs and rated their conspicuity on a 10-point scale (10=most obvious). A total of 55 NCPs with conspicuity of 5.2±2.8 was identified and 31 were assessed as positive vessel remodeling (PVR). Our previously developed method that combined multiscale vessel enhancement with 3D rolling balloon vessel tracking was applied to each cCTA volume to extract the coronary artery trees. Each extracted vessel was reformatted to a straightened volume composed of cCTA slices perpendicular to the vessel centerline using multi-planar reformation. The vessel wall gradient (VWG) at a given point was calculated as the maximum gradient along the radial direction from the vessel center to the wall and averaged over a ±45o sector. The minimum VWG around the vessel circumference was then found on each reformatted slice. The local minima of the VWG profile along each vessel were labeled as NCP candidates. Eleven features were designed to characterize the relative location along the coronary artery, shape, density, and VWGs of each NCP candidate. With a machine learning algorithm and a two-loop leave-one-case-out resampling method for training and testing, useful features were selected and combined into an NCP likelihood measure to differentiate true NCPs from FPs and to evaluate the performance of the detection system.
Our NCP prescreening method achieved a sensitivity of 80% (44/55) at an FP rate of 19.7 FPs/scan. An average of 3 features was selected. With the NCP likelihood measure, the FP rates reduced to 11.6, 5.8 and 3.7 FPs/scan at sensitivities of 80, 70, and 60%, respectively. At the same FP rates, the corresponding sensitivities for PVR were 77, 70, and 59%, respectively.
The study demonstrates the feasibility of our approach to the detection of NCPs in cCTA. Further investigation is underway to improve the accuracy and to validate the performance in a larger data set.
NCP detection remains challenging due to the large number of coronary arteries and multiple phase CT acquisition. CAD may be useful for radiologists in cCTA interpretation and risk assessment.
Radiological Society of North America 2012 Scientific Assembly and Annual Meeting; 11/2012
[Show abstract][Hide abstract] ABSTRACT: The purpose of the study was to determine the effectiveness of a collaborative educational, continuous quality improvement (CQI) initiative to increase appropriate use of coronary computed tomography angiography (CCTA).
Potential overuse of CCTA has prompted multisociety appropriate use criteria (AUC) publications.
This prospective, observational study was conducted with pre-intervention (July 2007 to June 2008), intervention (July 2008 to June 2010), and follow-up (July 2010 to December 2010) periods during which patients were enrolled in the Advanced Cardiovascular Imaging Consortium (ACIC) at 47 Michigan hospitals. Continuous education was provided to referring physicians. The possibility of losing third-party payer coverage in the absence of a measurable change in AUC was emphasized. AUC was compared between the 3 periods.
The study group included 25,387 patients. Compared with the pre-intervention period, there was a 23.4% increase in appropriate (61.3% to 80%, p < 0.0001), 60.3% decrease in inappropriate (14.6% to 5.8%, p < 0.0001), 40.8% decrease in uncertain (10.3% to 6.1%, p < 0.0001), and 41.7% decrease in unclassifiable (13.9% to 8.1%, p < 0.0001) scans during follow-up. Between pre-intervention and follow-up, change in CCTA referrals by provider specialty were cardiology (appropriate: 60.4% to 79.5%; inappropriate: 13% to 5.2%; p < 0.0001), internal medicine/family practice (appropriate: 51.1% to 70.4%; inappropriate: 20.2% to 12.5%; p < 0.0001), emergency medicine (appropriate: 83.6% to 91.6%; inappropriate: 9.1% to 0.6%; p < 0.0001), and other (appropriate: 61.1% to 83.2%; inappropriate: 18.6% to 5.9%; p < 0.0001).
Application of a systematic CQI and emphasis on possible loss of coverage were associated with a significant improvement in the proportion of CCTA examinations meeting AUC across referring physician specialties.
Journal of the American College of Cardiology 08/2012; 60(13):1185-91. DOI:10.1016/j.jacc.2012.06.008 · 16.50 Impact Factor
[Show abstract][Hide abstract] ABSTRACT: Coronary computed tomography angiography (CCTA) is an emerging noninvasive anatomical method for evaluation of patients with suspected coronary artery disease (CAD). Multicenter clinical registries are key to efforts to establish the role of CCTA in CAD diagnosis and management. The Advanced Cardiovascular Imaging Consortium (ACIC) is a statewide, multicenter collaborative quality initiative with the intent to establish quality and appropriate use of CCTA in Michigan.
The ACIC is sponsored by the Blue Cross Blue Shield of Michigan/Blue Care Network, and its 47 sites include imaging centers that offer CCTA and meet established structure and process standards for participation. Patients enrolled include those with suspected ischemia with or without known CAD, and individuals across the entire spectrum of CAD risk. Patient demographics, history, CCTA scan-related data and findings, and 90-day follow-up data are entered prospectively into a centralized database with strict validation tools and processes. Collaborative quality initiatives include radiation dose reduction and appropriate CCTA use by education and feedback to participating sites and referring physicians.
Across a wide range of institutions, the ACIC permits evaluation of "real-world" utilization and effectiveness of CCTA and examines an alternative, nontraditional approach to utilization management wherein physicians and payers collaborate to address the growing problem of cardiac imaging overutilization.
American heart journal 03/2012; 163(3):346-53. DOI:10.1016/j.ahj.2011.11.018 · 4.46 Impact Factor
[Show abstract][Hide abstract] ABSTRACT: Vessel segmentation is a fundamental step in an automated pulmonary
embolism (PE) detection system. The purpose of this study is to improve
the segmentation scheme for pulmonary vessels affected by PE and other
lung diseases. We have developed a multiscale hierarchical vessel
enhancement and segmentation (MHES) method for pulmonary vessel tree
extraction based on the analysis of eigenvalues of Hessian matrices.
However, it is difficult to segment the pulmonary vessels accurately
under suboptimal conditions, such as vessels occluded by PEs, surrounded
by lymphoid tissues or lung diseases, and crossing with other vessels.
In this study, we developed a new vessel refinement method utilizing
curved planar reformation (CPR) technique combined with optimal path
finding method (MHES-CROP). The MHES segmented vessels straightened in
the CPR volume was refined using adaptive gray level thresholding where
the local threshold was obtained from least-square estimation of a
spline curve fitted to the gray levels of the vessel along the
straightened volume. An optimal path finding method based on Dijkstra's
algorithm was finally used to trace the correct path for the vessel of
interest. Two and eight CTPA scans were randomly selected as training
and test data sets, respectively. Forty volumes of interest (VOIs)
containing "representative" vessels were manually segmented by a
radiologist experienced in CTPA interpretation and used as reference
standard. The results show that, for the 32 test VOIs, the average
percentage volume error relative to the reference standard was improved
from 32.9+/-10.2% using the MHES method to 9.9+/-7.9% using the
MHES-CROP method. The accuracy of vessel segmentation was improved
significantly (p<0.05). The intraclass correlation coefficient (ICC)
of the segmented vessel volume between the automated segmentation and
the reference standard was improved from 0.919 to 0.988. Quantitative
comparison of the MHES method and the MHES-CROP method with the
reference standard was also evaluated by the Bland-Altman plot. This
preliminary study indicates that the MHES-CROP method has the potential
to improve PE detection.
Proceedings of SPIE - The International Society for Optical Engineering 02/2012; 8315:21-. DOI:10.1117/12.912446 · 0.20 Impact Factor
[Show abstract][Hide abstract] ABSTRACT: PURPOSE/AIM
Highlight the Dana Point Classification of Pulmonary Hypertension with an emphasis on the CT manifestation of disease.
1. Introduction 2. Diagnosis and Classification System (Dana Point) 3. CT Findings of Pulmonary Hypertension 4. Treatment and Management 5. Summary and Conclusions
The Dana Point criteria offer a more clear pathophysiologic-based approach to clinical pulmonary hypertension. In the era of rapidly developing treatment for this spectrum of disease, it is increasingly important for the radiologist to be familiar with the CT characteristics of Pulmonary Hypertension in order to become an integral part of the management team.
Radiological Society of North America 2011 Scientific Assembly and Annual Meeting; 12/2011
[Show abstract][Hide abstract] ABSTRACT: PURPOSE/AIM
1. Review classification, clinical and imaging features of congenital conditions that may lead to sudden cardiac death 2. Review cardiac CT/MRI techniques used to evaluate patients with an emphasis on technical advances 3. Discuss the clinical potential of CT and MRI in evaluating these patients and to correlate clinical and imaging findings
The spectrum of congenital causes of sudden cardiac death includes genetic 1° cardiomyopathies (non-compaction, hypertrophic and arrhthymogenic right ventricular cardiomyopathies), and anomalous coronary arteries (interarterial or intramural course), and will be presented as clinical case series. The following will be discussed: Clinical significance, treatment and prognosis CT/MRI evaluation (protocols, imaging findings, and recent advances) Alternative diagnostic methods
Cardiac MR is an important tool for evaluation of genetic 1° cardiomyopathies providing assessment of myocardial morphology, function and tissue composition that guides clinical management in certain entities. CT is considered imaging modality of choice for non-invasive delineation of normal and anomalous coronary anatomy, and is useful for surgical planning vs. medical management. These imaging modalities can effectively identify causes of sudden cardiac death and alter clinical outcome.
Radiological Society of North America 2011 Scientific Assembly and Annual Meeting; 11/2011