We present an anthropomorphically accurate left ventricular (LV) phantom derived from human CT data to serve as the ground truth for the optimization and the spatial resolution quantification of a CT-derived regional strain metric (SQUEEZ) for the detection of regional wall motion abnormalities. Displacements were applied to the mesh points of a clinically derived end-diastolic LV mesh to create analytical end-systolic poses with physiologically accurate endocardial strains. Normal function as well as regional dysfunction of four sizes (1, 2/3, 1/2, and 1/3 AHA (American Heart Association) segments as core diameter), each exhibiting hypokinesia (70% reduction in strain) and subtle hypokinesia (40% reduction in strain), were simulated. Regional shortening (RSCT) estimates were obtained by registering the end-diastolic mesh to each simulated end-systolic mesh condition using a non-rigid registration algorithm. Ground-truth models of normal function and of hypokinesia were used to identify the optimal parameters in the registration algorithm, and to measure the accuracy of detecting regional dysfunction of varying sizes and severities. For normal LV function, RSCT values in all 16 AHA segments were accurate to within ±5%. For cases with regional dysfunction, the errors in RSCT around the dysfunctional region increased with decreasing size of dysfunctional tissue.
We present an anthropomorphically accurate left ventricular (LV) phantom derived from human CT data to serve as the ground truth for the optimization and the spatial resolution quantification of a CT-derived regional strain metric (SQUEEZ) for the detection of regional wall motion abnormalities. Displacements were applied to the mesh points of a clinically derived end-diastolic LV mesh to create analytical end-systolic poses with physiologically accurate endocardial strains. Normal function as well as regional dysfunction of four sizes (1, 2/3, 1/2, and 1/3 AHA (American Heart Association) segments as core diameter), each exhibiting hypokinesia (70% reduction in strain) and subtle hypokinesia (40% reduction in strain), were simulated. Regional shortening (RSCT) estimates were obtained by registering the end-diastolic mesh to each simulated end-systolic mesh condition using a non-rigid registration algorithm. Ground-truth models of normal function and of hypokinesia were used to identify the optimal parameters in the registration algorithm, and to measure the accuracy of detecting regional dysfunction of varying sizes and severities. For normal LV function, RSCT values in all 16 AHA segments were accurate to within ±5%. For cases with regional dysfunction, the errors in RSCT around the dysfunctional region increased with decreasing size of dysfunctional tissue.The current gold-standard for the non-invasive assessment of regional LV function is cardiovascular magnetic resonance (CMR) tagging 7-10 . However, CMR requires extended breath holds, acquisition over multiple heart beats, and manual contouring 7,11 . The growing number of patients with metallic medical device implants further limits the clinical use of CMR.Recent advances in x-ray computed tomography (CT) have made possible the acquisition of an entire 3D volume of the heart from a single table position in ~140 ms, which implies a series of functional images spanning the full cardiac cycle can be obtained within a single heartbeat [12][13][14][15][16] .Additionally, the spatial resolution (0.4 x 0.4 x 0.6 mm 3 nominal voxel size) allows for the detection and tracking of the fine endocardial texture comprising trabeculae carneae and papillary muscles 17 . The drawback of CT is patient exposure to ionizing radiation; however, due to recent advancements in CT technology, especially in the last 5 years, the average dose received by a patient from a functional cardiac CT scan is ~3 mSv, which is the average dose received from natural sources in a year 18 . SQUEEZ 17 is a new method introduced to measure regional endocardial strain from 4DCT images acquired with routine clinical protocols. SQUEEZ exploits the high fidelity of x-ray CT to track features of the endocardium, which are used by a non-rigid point set registration technique 19 to derive displacements of points on the endocardium across the cardiac cycle. This displacement estimate is used to obtain information on the regional strain of the endocardium. SQUEEZ has shown to be capable of differentiating ...
We present a method to leverage the high fidelity of computed tomography (CT) to quantify regional left ventricular function using topography variation of the endocardium as a surrogate measure of strain. 4DCT images of 10 normal and 10 abnormal subjects, acquired with standard clinical protocols, are used. The topography of the endocardium is characterized by its regional values of fractal dimension (F D), computed using a box-counting algorithm developed in-house. The average F D in each of the 16 American Heart Association segments is calculated for each subject as a function of time over the cardiac cycle. The normal subjects show a peak systolic percentage change in F D of 5.9% AE 2% in all free-wall segments, whereas the abnormal cohort experiences a change of 2% AE 1.2% (p < 0.00001). Septal segments, being smooth, do not undergo large changes in F D. Additionally, a principal component analysis is performed on the temporal profiles of F D to highlight the possibility for unsupervised classification of normal and abnormal function. The method developed is free from manual contouring and does not require any feature tracking or registration algorithms. The F D values in the free-wall segments correlated well with radial strain and with endocardial regional shortening measurements.
Background: Cardiac resynchronization therapy (CRT) is an effective treatment for patients with heart failure; however, 30% of patients do not respond to the treatment. We sought to derive patient-specific left-ventricle (LV) maps of lead placement scores (LPS) that highlight target pacing lead sites for achieving a higher probability of CRT response. Methods: Eighty-two subjects recruited for the ImagingCRT trial were retrospectively analyzed. All 82 subjects had two contrast-enhanced full-cardiac cycle 4DCT scans: a baseline and a 6-month follow-up scan. CRT response was defined as a reduction in CT-derived end-systolic volume ≥15%. Eight LV features derived from the baseline scans were used to train a support vector machine (SVM) via a bagging approach. An LPS map over the LV was created for each subject as a linear combination of the SVM feature weights and the subject's own feature vector. Performance for distinguishing responders was performed on the original 82 subjects. Results: Fifty-two (63%) subjects were responders. Subjects with an LPS ≤ Q1 (lower-quartile) had a posttest probability of responding of 14% (3/21), while subjects with an LPS ≥ Q3 (upper-quartile) had a posttest probability of responding of 90% (19/21). Subjects with Q1 < LPS < Q3 had a posttest probability of responding that was essentially unchanged from the pretest probability (75% vs 63%, p=0.2). An LPS threshold that maximized the geometric mean of true-negative and true-positive rates identified 26/30 of the non-responders. The AUC of the ROC curve for identifying responders with an LPS threshold was 87%. Conclusions: An LPS map was defined using 4DCT-derived features of LV mechanics. The LPS correlated with CRT response, reclassifying 25% of the subjects into low-probability of response, 25% into high-probability of response, and 50% unchanged. These encouraging results highlight the potential utility of 4DCT in guiding patient selection for CRT. The present findings need verification in larger independent data sets and prospective trials.
BackgroundThe presence of left ventricular (LV) wall motion abnormalities (WMA) is an independent indicator of adverse cardiovascular events in patients with cardiovascular diseases. We develop and evaluate the ability to detect cardiac wall motion abnormalities (WMA) from dynamic volume renderings (VR) of clinical 4D computed tomography (CT) angiograms using a deep learning (DL) framework.MethodsThree hundred forty-three ECG-gated cardiac 4DCT studies (age: 61 ± 15, 60.1% male) were retrospectively evaluated. Volume-rendering videos of the LV blood pool were generated from 6 different perspectives (i.e., six views corresponding to every 60-degree rotation around the LV long axis); resulting in 2058 unique videos. Ground-truth WMA classification for each video was performed by evaluating the extent of impaired regional shortening visible (measured in the original 4DCT data). DL classification of each video for the presence of WMA was performed by first extracting image features frame-by-frame using a pre-trained Inception network and then evaluating the set of features using a long short-term memory network. Data were split into 60% for 5-fold cross-validation and 40% for testing.ResultsVolume rendering videos represent ~800-fold data compression of the 4DCT volumes. Per-video DL classification performance was high for both cross-validation (accuracy = 93.1%, sensitivity = 90.0% and specificity = 95.1%, κ: 0.86) and testing (90.9, 90.2, and 91.4% respectively, κ: 0.81). Per-study performance was also high (cross-validation: 93.7, 93.5, 93.8%, κ: 0.87; testing: 93.5, 91.9, 94.7%, κ: 0.87). By re-binning per-video results into the 6 regional views of the LV we showed DL was accurate (mean accuracy = 93.1 and 90.9% for cross-validation and testing cohort, respectively) for every region. DL classification strongly agreed (accuracy = 91.0%, κ: 0.81) with expert visual assessment.ConclusionsDynamic volume rendering of the LV blood pool combined with DL classification can accurately detect regional WMA from cardiac CT.
Background Estimates of regional left ventricular (LV) strains provide additional information to global function parameters such as ejection fraction (EF) and global longitudinal strain (GLS) and are more sensitive in detecting abnormal regional cardiac function. The accurate and reproducible assessment of regional cardiac function has implications in the management of various cardiac diseases such as heart failure, myocardial ischemia, and dyssynchrony. Purpose To develop a method that yields highly reproducible, high‐resolution estimates of regional endocardial strains from 4DCT images. Methods A method for estimating regional LV endocardial circumferential false(εccfalse)$( {{\epsilon }_{cc}} )$ and longitudinal (εll${\epsilon }_{ll}$) strains from 4DCT was developed. Point clouds representing the LV endocardial surface were extracted for each time frame of the cardiac cycle from 4DCT images. 3D deformation fields across the cardiac cycle were obtained by registering the end diastolic point cloud to each subsequent point cloud in time across the cardiac cycle using a 3D point‐set registration technique. From these deformation fields, εccandεll${\epsilon }_{cc}\ {\rm{and\ }}{\epsilon }_{ll}$ were estimated over the entire LV endocardial surface by fitting an affine transformation with maximum likelihood estimation. The 4DCT‐derived strains were compared with strains estimated in the same subjects by cardiac magnetic resonance (CMR); twenty‐four subjects had CMR scans followed by 4DCT scans acquired within a few hours. Regional LV circumferential and longitudinal strains were estimated from the CMR images using a commercially available feature tracking software (cvi42). Global circumferential strain (GCS) and global longitudinal strain (GLS) were calculated as the mean of the regional strains across the entire LV for both modalities. Pearson correlation coefficients and Bland‐Altman analyses were used for comparisons. Intraclass correlation coefficients (ICC) were used to assess the inter‐ and intraobserver reproducibility of the 4DCT‐derived strains. Results The 4DCT‐derived regional strains correlated well with the CMR‐derived regional strains (εcc${\epsilon }_{cc}$: r = 0.76, p < 0.001; εll${\epsilon }_{ll}$: r = 0.64, p < 0.001). A very strong correlation was found between 4DCT‐derived GCS and 4DCT‐derived EF (r = −0.96; p < 0.001). The 4DCT‐derived strains were also highly reproducible, with very low inter‐ and intraobserver variability (intraclass correlation coefficients in the range of [0.92, 0.99]). Conclusions We have developed a novel method to estimate high‐resolution regional LV endocardial circumferential and longitudinal strains from 4DCT images. Except for the definition of the mitral valve and LV outflow tract planes, the method is completely user independent, thus yielding highly reproducible estimates of endocardial strain. The 4DCT‐derived strains correlated well with those estimated using a commercial CMR feature tracking software. The promising results reported in this study highli...
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