Four‐dimensional computed tomography of the left ventricle, Part I: Motion artifact reduction

Pack, Jed D.; Manohar, Ashish; Ramani, Sathish; Claus, Bernhard; Yin, Zhye; Contijoch, Francisco; Schluchter, Andrew; McVeigh, Elliot R.

doi:10.1002/mp.15709

Cited by 8 publications

(18 citation statements)

References 25 publications

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“…The resulting images clearly manifested the expected motion artifact characteristics seen in images reconstructed from real dynamic data, including "double-wall" and "stationary-wall" artifacts and distortions that rotate in concert with the orientation of the gantry angle. 26 Intra window motion is included in the linear interpolation of sinogram data during synthetic sinogram creation. The difference between the continuous sinogram and the interpolated sinogram yields artifacts in the reconstructed images that are imperceptible compared with the larger "double-wall" and "stationary-wall" artifacts 27 ; these larger artifacts are the primary sources of error in the estimation of mechanical activation times of wall motion.…”

Section: Dynamic Raw Data Synthesis and Image Reconstructionmentioning

confidence: 99%

Four‐dimensional computed tomography of the left ventricle, Part II: Estimation of mechanical activation times

et al. 2022

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Purpose We demonstrate the viability of a four‐dimensional X‐ray computed tomography (4DCT) imaging system to accurately and precisely estimate mechanical activation times of left ventricular (LV) wall motion. Accurate and reproducible timing estimates of LV wall motion may be beneficial in the successful planning and management of cardiac resynchronization therapy (CRT). Methods We developed an anthropomorphically accurate in silico LV phantom based on human CT images with programmed septal‐lateral wall dyssynchrony. Twenty‐six temporal phases of the in silico phantom were used to sample the cardiac cycle of 1 s. For each of the 26 phases, 1 cm thick axial slabs emulating axial CT image volumes were extracted, 3D printed, and imaged using a commercially available CT scanner. A continuous dynamic sinogram was synthesized by blending sinograms from these static phases; the synthesized sinogram emulated the sinogram that would be acquired under true continuous phantom motion. Using the synthesized dynamic sinogram, images were reconstructed at 70 ms intervals spanning the full cardiac cycle; these images exhibited expected motion artifact characteristics seen in images reconstructed from real dynamic data. The motion corrupted images were then processed with a novel motion correction algorithm (ResyncCT) to yield motion corrected images. Five pairs of motion uncorrected and motion corrected images were generated, each corresponding to a different starting gantry angle (0 to 180 degrees in 45 degree increments). Two line profiles perpendicular to the endocardial surface were used to sample local myocardial motion trajectories at the septum and the lateral wall. The mechanical activation time of wall motion was defined as the time at which the endocardial boundary crossed a fixed position defined on either of the two line profiles while moving toward the center of the LV during systolic contraction. The mechanical activation times of these myocardial trajectories estimated from the motion uncorrected and the motion corrected images were then compared with those derived from the static images of the 3D printed phantoms (ground truth). The precision of the timing estimates was obtained from the five different starting gantry angle simulations. Results The range of estimated mechanical activation times observed across all starting gantry angles was significantly larger for the motion uncorrected images than for the motion corrected images (lateral wall: 58 ± 15 ms vs 12 ± 4 ms, p < 0.005; septal wall: 61 ± 13 ms vs 13 ± 9 ms, p < 0.005). Conclusions 4DCT images processed with the ResyncCT motion correction algorithm yield estimates of mechanical activation times of LV wall motion with significantly improved accuracy and precision. The promising results reported in this study highlight the potential utility of 4DCT in estimating the timing of mechanical events of interest for CRT guidance.

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Section: Dynamic Raw Data Synthesis and Image Reconstructionmentioning

confidence: 99%

Four‐dimensional computed tomography of the left ventricle, Part II: Estimation of mechanical activation times

et al. 2022

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Section: Discussionmentioning

confidence: 99%

“…Despite the excellent temporal resolution of the dual-source scanner (66 ms per frame), wider detector scanners (256 or 320 detector rows) with full heart coverage from a single table position may be better suited for this application, especially with the recent innovations in motion estimation and motion compensation technology. 41,42 All 4DCT images used in this study were acquired and reconstructed with the same CT imaging system; this was tremendously advantageous in facilitating a direct comparison of LPS values derived from 4DCT scans of similar image characteristics. However, different scanners yield images of different image quality which could in turn affect the computed LPS values; therefore, to standardize the LPS model across different imaging centers and vendors, future studies will need to explore the sensitivity of the LPS estimates to varying image qualities.…”

Section: Limitationsmentioning

confidence: 99%

Prediction of Cardiac Resynchronization Therapy Response Using a Lead Placement Score Derived From 4-Dimensional Computed Tomography

Manohar

Colvert

Yang

et al. 2022

Circ: Cardiovascular Imaging

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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 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 (Empiric Versus Imaging Guided Left Ventricular Lead Placement in Cardiac Resynchronization Therapy) were retrospectively analyzed. All 82 subjects had 2 contrast-enhanced full cardiac cycle 4-dimensional computed tomography scans: a baseline and a 6-month follow-up scan. CRT response was defined as a reduction in computed tomography–derived end-systolic volume ≥15%. Eight left ventricle features derived from the baseline scans were used to train a support vector machine via a bagging approach. An LPS map over the left ventricle was created for each subject as a linear combination of the support vector machine 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≤Q 1 (lower-quartile) had a posttest probability of responding of 14% (3/21), while subjects with an LPS≥ Q 3 (upper-quartile) had a posttest probability of responding of 90% (19/21). Subjects with Q 1 <LPS<Q 3 had a posttest probability of responding that was essentially unchanged from the pretest probability (75% versus 63%, P =0.2). An LPS threshold that maximized the geometric mean of true-negative and true-positive rates identified 26/30 of the nonresponders. The area under the curve of the receiver operating characteristic curve for identifying responders with an LPS threshold was 87%. Conclusions: An LPS map was defined using 4-dimensional computed tomography–derived features of left ventricular 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 4-dimensional computed tomography in guiding patient selection for CRT. The present findings need verification in larger independent data sets and prospective trials.

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“…We anticipate the performance of the developed 4DCT strain estimation method to improve with higher resolution, motion‐corrected data 14 subjected to new deep learning networks for segmentation or direct strain estimation. Examination of the dependence of accuracy on dose will also permit the establishment of the minimum required dose for robust strain estimates.…”

Section: Discussionmentioning

confidence: 99%

“…38 The high reproducibility of both LV strains and volumes helps solve a long-standing shortcoming of nonreproducible quantitative function measurements from echocardiography. [39][40][41] We anticipate the performance of the developed 4DCT strain estimation method to improve with higher resolution, motion-corrected data 14 subjected to new deep learning networks for segmentation or direct strain estimation. Examination of the dependence of accuracy on dose will also permit the establishment of the minimum required dose for robust strain estimates.…”

Section: Dct-derived Regional LV Endocardial Strain Estimationmentioning

confidence: 99%

Regional left ventricular endocardial strains estimated from low‐dose 4DCT: Comparison with cardiac magnetic resonance feature tracking

et al. 2022

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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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Four‐dimensional computed tomography of the left ventricle, Part I: Motion artifact reduction

Cited by 8 publications

References 25 publications

Four‐dimensional computed tomography of the left ventricle, Part II: Estimation of mechanical activation times

Four‐dimensional computed tomography of the left ventricle, Part II: Estimation of mechanical activation times

Prediction of Cardiac Resynchronization Therapy Response Using a Lead Placement Score Derived From 4-Dimensional Computed Tomography

Regional left ventricular endocardial strains estimated from low‐dose 4DCT: Comparison with cardiac magnetic resonance feature tracking

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