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Cardiac magnetic resonance myocardial perfusion imaging can detect coronary artery disease and is an alternative to single-photon emission computed tomography or positron emission tomography. However, the complex, non-linear MR signal and the lack of robust quantification of myocardial blood flow have hindered its widespread clinical application thus far. Recently, a new Bayesian approach was developed for brain imaging and evaluation of perfusion indexes (Kudo et al., 2014). In addition to providing accurate perfusion measurements, this probabilistic approach appears more robust than previous approaches, particularly due to its insensitivity to bolus arrival delays. We assessed the performance of this approach against a well-known and commonly deployed model-independent method based on the Fermi function for cardiac magnetic resonance myocardial perfusion imaging. The methods were first evaluated for accuracy and precision using a digital phantom to test them against the ground truth; next, they were applied in a group of coronary artery disease patients. The Bayesian method can be considered an appropriate model-independent method with which to estimate myocardial blood flow and delays. The digital phantom comprised a set of synthetic time-concentration curve combinations generated with a 2-compartment exchange model and a realistic combination of perfusion indexes, arterial input dynamics, noise and delays collected from the clinical dataset. The myocardial blood flow values estimated with the two methods showed an excellent correlation coefficient ( r 2 > 0.9) under all noise and delay conditions. The Bayesian approach showed excellent robustness to bolus arrival delays, with a similar performance to Fermi modeling when delays were considered. Delays were better estimated with the Bayesian approach than with Fermi modeling. An in vivo analysis of coronary artery disease patients revealed that the Bayesian approach had an excellent ability to distinguish between abnormal and normal myocardium. The Bayesian approach was able to discriminate not only flows but also delays with increased sensitivity by offering a clearly enlarged range of distribution for the physiologic parameters., Competing Interests: SG and M-PJ were employed by company Siemens Medical Solutions USA, Inc. TB was employed by Olea Medical. The remaining authors declare that the research was conducted in the absence of any commercial or financial relationships that could be construed as a potential conflict of interest., (Copyright © 2021 Daviller, Boutelier, Giri, Ratiney, Jolly, Vallée, Croisille and Viallon.)

Objectives: To validate deformable registration algorithms (DRAs) for cine balanced steady-state free precession (bSSFP) assessment of global longitudinal strain (GLS) and global circumferential strain (GCS) using harmonic phase (HARP) cardiovascular magnetic resonance as standard of reference (SoR)., Methods: Seventeen patients and 17 volunteers underwent short axis stack and 2-/4-chamber cine bSSFP imaging with matching slice long-axis and mid-ventricular spatial modulation of magnetization (SPAMM) myocardial tagging. Inverse DRA was applied on bSSFP data for assessment of GLS and GCS while myocardial tagging was processed using HARP. Intra- and inter-observer variability assessment was based on repeated analysis by a single observer and analysis by a second observer, respectively. Standard semi-automated short axis stack segmentation was performed for analysis of left ventricular (LV) volumes and ejection fraction (EF)., Results: DRA demonstrated strong relationships to HARP for myocardial GLS (R 2  = 0.75; p < 0.0001) and endocardial GLS (R 2  = 0.61; p < 0.0001). GCS result comparison also demonstrated significant relationships between DRA and HARP for myocardial strain (R 2  = 0.61; p < 0.0001) and endocardial strain (R 2  = 0.51; p < 0.0001). Both methods demonstrated small systematic errors for intra- and inter-observer variability but DRA demonstrated consistently lower CV. Global LVEF was significantly lower (p = 0.0099) in patients (53.7%; IQR 43.9/64.0%) than in healthy volunteers (62.6%; IQR 61.1/66.2%). DRA and HARP strain data demonstrated significant relationships to LVEF., Conclusions: Non-rigid deformation method-based DRA provides a reliable measure of peak systolic GCS and GLS based on cine bSSFP with superior intra- and inter-observer reproducibility compared to HARP., Key Point: • Myocardial strain can be reliably analyzed using inverse deformable registration algorithms (DRAs) on cine CMR. • Inverse DRA-derived strain shows higher reproducibility than tagged CMR. • DRA and tagged CMR-based myocardial strain demonstrate strong relationships to global left ventricular function.

Background: Doppler based mitral annular velocities are an integral part of echocardiographic left ventricular diastolic function assessment. Although these measurements can be obtained by phase contrast cardiac magnetic resonance imaging (PC-CMR), this approach has limitations. The aims of this study were to assess the accuracy and reproducibility of a high temporal resolution steady-state free precession (SSFP) cine acquisition coupled with semi-automated mitral annular tracking to measure tissue velocity, and compare to echocardiography as the reference method., Methods: High temporal resolution (17 ms) 4-chamber cines were acquired in 25 volunteers using retrospective and prospective gating on a 3.0 T magnet. Mitral annular early (e') and late (a') tissue velocities were derived using a novel algorithm to semi-automatically detect the mitral valve insertion points and track its motion. Additionally, PC-CMR was used to measure mitral inflow early diastolic (E) velocity. Those measurements were also obtained using echocardiography based pulsed and tissue Doppler techniques, on the same day., Results: Subjects were on average 34 ± 14 years-old (48% male). The lateral annulus e' measurements had the best agreement with echocardiography with a concordance correlation coefficient (CCC) of 0.76 and 0.75 for prospectively and retrospectively gated cine CMR respectively. There was no significant difference in the lateral annular tissue velocities between echocardiography (13.8 ± 3.7 cm/s) and prospective (13.4 ± 3.7 cm/s) or retrospective (14.0 ± 3.7) acquisitions. Similarly, CMR measurement of E/e' (a surrogate marker for LV filling pressures) using the lateral e' velocity showed moderate agreement with echocardiography (CCC of 0.56 and 0.51 for prospective and retrospective acquisitions respectively) without a significant difference in ratios (5.3 ± 1.6 and 5.0 ± 1.3) compared to echocardiography (5.2 ± 1.4). Intra- and inter-observer reproducibility of the CMR-based annular velocity measurements was good., Conclusion: Measurements of mitral annular tissue velocities can be obtained from SSFP 4-chamber cine images using a semi-automated annular tracking algorithm, and demonstrates moderate agreement with echocardiography. The semi-automated method can provide quantitative mitral annular velocity measurements directly from conventional cine images, thereby providing additional clinically relevant information. The accuracy of this method in patients with diastolic dysfunction remains to be determined., (Copyright © 2018 Elsevier Inc. All rights reserved.)

Purpose To measure left ventricular (LV) myocardial strain with cine magnetic resonance (MR) imaging and a deformable registration algorithm (DRA) and to assess the prognostic value of myocardial strain in patients with light-chain (AL) amyloidosis. Materials and Methods In this prospective study, 78 consecutive patients with AL amyloidosis who underwent contrast material-enhanced cardiac MR imaging were enrolled at West China Hospital. LV myocardial strains and late gadolinium enhancement (LGE) were evaluated. Association between myocardial strain and all-cause mortality was analyzed with the stepwise Cox regression model. Results Global longitudinal strain (GLS) and global circumferential strain (GCS) were significantly lower in the no or nonspecific LGE group compared with the subendocardial LGE and transmural LGE groups (mean GLS, -10% ± 3 [standard deviation] vs -7% ± 3 vs -4% ± 1; P < .001) (mean GCS, -13% ± 3 vs -11% ± 3 vs -7% ± 2; P < .001). GLS and GCS were reduced in patients without clinical cardiac amyloidosis (mean GLS, -13% ± 3 vs -16% ± 2; P = .005) (mean GCS, -16% ± 1 vs -19% ± 2; P = .02). Circumferential and radial strains were impaired in basal segments in accordance with the distribution of LGE. Multivariate Cox analysis revealed that GCS (hazard ratio [HR] = 1.16 per 1% absolute decrease; 95% confidence interval [CI]: 1.03, 1.31; P = .02) and the presence of transmural LGE (HR = 1.75; 95% CI: 1.10, 2.80; P = .02) were independent predictors of all-cause mortality after adjustment for LV ejection fraction, right ventricular ejection fraction, LV mass index, GLS, and global radial strain. Conclusion Strain parameters derived with cine MR imaging-based DRA may be a new noninvasive imaging marker with which to evaluate the extent of cardiac amyloid infiltration and may offer independent prognostic information for all-cause mortality in patients with AL amyloidosis., (© RSNA, 2018 Online supplemental material is available for this article.)

UK Biobank, a large cohort study, plans to acquire 100,000 cardiac MRI studies by 2020. Although fully-automated left ventricular (LV) analysis was performed in the original acquisition, this was not designed for unsupervised incorporation into epidemiological studies. We sought to evaluate automated LV mass and volume (Siemens syngo InlineVF versions D13A and E11C), against manual analysis in a substantial sub-cohort of UK Biobank participants. Eight readers from two centers, trained to give consistent results, manually analyzed 4874 UK Biobank cases for LV end-diastolic volume (EDV), end-systolic volume (ESV), stroke volume (SV), ejection fraction (EF) and LV mass (LVM). Agreement between manual and InlineVF automated analyses were evaluated using Bland-Altman analysis and the intra-class correlation coefficient (ICC). Tenfold cross-validation was used to establish a linear regression calibration between manual and InlineVF results. InlineVF D13A returned results in 4423 cases, whereas InlineVF E11C returned results in 4775 cases and also reported LVM. Rapid visual assessment of the E11C results found 178 cases (3.7%) with grossly misplaced contours or landmarks. In the remaining 4597 cases, LV function showed good agreement: ESV -6.4 ± 9.0 ml, 0.853 (mean ± SD of the differences, ICC) EDV -3.0 ± 11.6 ml, 0.937; SV 3.4 ± 9.8 ml, 0.855; and EF 3.5 ± 5.1%, 0.586. Although LV mass was consistently overestimated (29.9 ± 17.0 g, 0.534) due to larger epicardial contours on all slices, linear regression could be used to correct the bias and improve accuracy. Automated InlineVF results can be used for case-control studies in UK Biobank, provided visual quality control and linear bias correction are performed. Improvements between InlineVF D13A and InlineVF E11C show the field is rapidly advancing, with further improvements expected in the near future.

Patients with drug-refractory heart failure can greatly benefit from cardiac resynchronization therapy (CRT). A CRT device can resynchronize the contractions of the left ventricle (LV) leading to reduced mortality. Unfortunately, 30%-50% of patients do not respond to treatment when assessed by objective criteria such as cardiac remodeling. A significant contributing factor is the suboptimal placement of the LV lead. It has been shown that placing this lead away from scar and at the point of latest mechanical activation can improve response rates. This paper presents a comprehensive and highly automated system that uses scar and mechanical activation to plan and guide CRT procedures. Standard clinical preoperative magnetic resonance imaging is used to extract scar and mechanical activation information. The data are registered to a single 3-D coordinate system and visualized in novel 2-D and 3-D American Heart Association plots enabling the clinician to select target segments. During the procedure, the planning information is overlaid onto live fluoroscopic images to guide lead deployment. The proposed platform has been used during 14 CRT procedures and validated on synthetic, phantom, volunteer, and patient data.

Purpose: We aim at developing a framework for the validation of a subject-specific multi-physics model of liver tumor radiofrequency ablation (RFA)., Methods: The RFA computation becomes subject specific after several levels of personalization: geometrical and biophysical (hemodynamics, heat transfer and an extended cellular necrosis model). We present a comprehensive experimental setup combining multimodal, pre- and postoperative anatomical and functional images, as well as the interventional monitoring of intra-operative signals: the temperature and delivered power., Results: To exploit this dataset, an efficient processing pipeline is introduced, which copes with image noise, variable resolution and anisotropy. The validation study includes twelve ablations from five healthy pig livers: a mean point-to-mesh error between predicted and actual ablation extent of 5.3 ± 3.6 mm is achieved., Conclusion: This enables an end-to-end preclinical validation framework that considers the available dataset.

Background: In patients with cancer receiving potentially cardio-toxic chemotherapy, measurements of left ventricular (LV) circumferential or longitudinal strain are often used clinically to identify myocardial dysfunction. Using a new software algorithm, we sought to determine in individuals receiving treatment for cancer the association between automated assessments of LV mean mid-wall circumferential strain and conventional measures of LV ejection fraction (EF) both obtained from cardiovascular magnetic resonance (CMR) cine balanced steady-state free-precession (bSSFP) white-blood acquisitions., Methods: Before and 3 months after initiating treatment with potentially cardio-toxic chemotherapy, 72 individuals (aged 54 ± 14 years with breast cancer [39%], lymphoma [49%], or sarcoma [12%]) underwent serial CMR cine bSSFP assessments of LV volumes and EF, and mean mid-wall circumferential strain determined from these same cine images as well as from additional tagged CMR images. On the cine images, assessments of strain were obtained using the newly developed deformation-based segmentation algorithm. Assessments of LV volumes/EF from the cine images and strain from tagged CMR were accomplished using commercially available software. All measures were analyzed in a blinded fashion independent of one another., Results: Acceptable measures for the automated assessments of mean mid-wall circumferential strain from the cine images were obtained in 142 of 144 visits (98.6%) with an overall analysis time averaging 6:47 ± 1:06 min. The results from these automated measures averaged -18.8 ± 2.9 at baseline and -17.6 ± 3.1 at 3 months (p = 0.001). Left ventricular EF declined slightly from 65 ± 7% at baseline to 62 ± 7% at 3 months (p = 0.0002). The correlation between strain from cine imaging and LVEF was r = -0.61 (p < 0.0001). In addition, the 3-month changes in LV strain and LVEF were correlated (r = -0.49; p < 0.0001). The correlation between cine and tagged derived assessments of strain was r = 0.23; p = 0.01., Conclusions: Automated measures of LV mean mid-wall circumferential strain can be obtained in 6¾ minutes from cine bSSFP LV short-axis images (used concurrently to assess LV volumes and EF) in 98.6% of patients receiving treatment for cancer with potentially cardio-toxic chemotherapy. These cine derived measures of circumferential strain correlate with early subclinical declines in LVEF.

The purpose of this study was to assess the consistency of semi-automated myocardial strain analysis by prototype software across field strengths, temporal resolutions, and examinations. 35 volunteers (48 ± 13 years; 20% women) and 25 patients (54 ± 12 years; 44% women) without significant cardiac dysfunction underwent cine cardiac magnetic resonance imaging (CMR) at 1.5 T with a temporal resolution of 39.2 msec. 34 subjects also underwent imaging at 3.0 T; 16 had repeat examinations within 14 days; and 9 underwent CMR with temporal resolutions of 12.5 and 39.2 msec on the same day. Prototype heart deformation analysis (HDA) software was used to retrospectively quantify strain from segmented balanced steady state free precession (bSSFP) cinegraphic images. Myocardial contours were automatically generated on short axis images and drawn at end-diastole by two independent reviewers on long-axis images. Contours were automatically propagated throughout the cardiac cycle. Global and regional peak systolic strain were compared across observers, field strengths, temporal resolutions, and examinations. Inter-observer agreement was excellent (ICC > 0.87, p < 0.01). Inter-examination variability was low, ranging from 1.7 (1.0-2.4)% to 2.5 (1.9-3.1)%, except for radial strain: 9.2 (7.6-10.5)%. Most global and regional strain values were not significantly different across field strengths and temporal resolutions (p > 0.05). Normal global peak systolic strain values with HDA were -25.0 (-24.0 to -26.1)% (LV circumferential), 60.5 (55.3 to 65.6)% (LV radial), -22.3 (-20.5 to - 24.0)% (LV longitudinal), and -26.0 (-23.8 to -28.2)% (RV longitudinal). HDA prototype software enabled efficient and consistent quantification of myocardial strain from conventional bSSFP cine CMR data, demonstrating clinical feasibility.

Objectives: To evaluate deformable registration algorithms (DRA)-based quantification of cine steady-state free-precession (SSFP) for myocardial strain assessment in comparison with feature-tracking (FT) and speckle-tracking echocardiography (STE)., Methods: Data sets of 28 patients/10 volunteers, undergoing same-day 1.5T cardiac MRI and echocardiography were included. LV global longitudinal (GLS), circumferential (GCS) and radial (GRS) peak systolic strain were assessed on cine SSFP data using commercially available FT algorithms and prototype DRA-based algorithms. STE was applied as standard of reference for accuracy, precision and intra-/interobserver reproducibility testing., Results: DRA showed narrower limits of agreement compared to STE for GLS (-4.0 [-0.9,-7.9]) and GCS (-5.1 [1.1,-11.2]) than FT (3.2 [11.2,-4.9]; 3.8 [13.9,-6.3], respectively). While both DRA and FT demonstrated significant differences to STE for GLS and GCS (all p<0.001), only DRA correlated significantly to STE for GLS (r=0.47; p=0.006). However, good correlation was demonstrated between MR techniques (GLS:r=0.74; GCS:r=0.80; GRS:r=0.45, all p<0.05). Comparing DRA with FT, intra-/interobserver coefficient of variance was lower (1.6 %/3.2 % vs. 6.4 %/5.7 %) and intraclass-correlation coefficient was higher. DRA GCS and GRS data presented zero variability for repeated observations., Conclusions: DRA is an automated method that allows myocardial deformation assessment with superior reproducibility compared to FT., Key Points: • Inverse deformable registration algorithms (DRA) allow myocardial strain analysis on cine MRI. • Inverse DRA demonstrated superior reproducibility compared to feature-tracking (FT) methods. • Cine MR DRA and FT analysis demonstrate differences to speckle-tracking echocardiography • DRA demonstrated better correlation with STE than FT for MR-derived global strain data.

The cine magnetic resonance imaging based technique feature tracking-cardiac magnetic resonance (FT-CMR) is emerging as a novel, simple and robust method to evaluate myocardial strain. We investigated the distribution characteristics of left-ventricular myocardial strain using a novel cine MRI based deformation registration algorithm (DRA) in a cohort of healthy Chinese subjects. A total of 130 healthy Chinese subjects were enrolled. Three components of orthogonal strain (radial, circumferential, longitudinal) of the left ventricle were analyzed using DRA on steady-state free precession cine sequence images. A distinct transmural circumferential strain gradient was observed in the left ventricle that showed universal increment from the epicardial to endocardial myocardial wall (epiwall: -15.4 ± 1.9%; midwall: -18.8 ± 2.0%; endowall: -22.3 ± 2.3%, P < 0.001). Longitudinal strain showed a similar trend from epicardial to endocardial layers (epiwall: -16.0 ± 2.9%; midwall: -15.6 ± 2.7%; endowall: -14.8 ± 2.4%, P < 0.001), but radial strain had a very heterogeneous distribution and variation. In the longitudinal direction from the base to the apex of the left ventricle, there was a trend of decreasing peak systolic longitudinal strain (basal: -23.3 ± 4.6%; mid: -13.7 ± 7.3%; apical: -13.2 ± 5.5%; P < 0.001). In conclusion, there are distinct distribution patterns of circumferential and longitudinal strain within the left ventricle in healthy Chinese subjects. These distribution patterns of strain may provide unique profiles for further study in different types of myocardial disease.

Purpose To quantify myocardial extracellular volume (ECV) by using cardiac magnetic resonance (MR) imaging in thalassemia major and to investigate the relationship between ECV and myocardial iron overload. Materials and Methods With institutional review board approval and informed consent, 30 patients with thalassemia major (mean age ± standard deviation, 34.6 years ± 9.5) and 10 healthy control subjects (mean age, 31.5 years ± 4.4) were prospectively recruited (clinicaltrials.gov identification number NCT02090699). Nineteen patients (63.3%) had prior myocardial iron overload (defined as midseptal T2* < 20 msec on any prior cardiac MR images). Cardiac MR imaging at 1.5 T included cine steady-state free precession for ventricular function, T2* for myocardial iron quantification, and unenhanced and contrast material-enhanced T1 mapping. ECV was calculated with input of the patient's hematocrit level. Peak systolic global longitudinal strain by means of speckle tracking was assessed with same-day transthoracic echocardiography. Statistical analysis included use of the two-sample t test, Fisher exact test, and Spearman correlation. Results Unenhanced T1 values were significantly lower in patients with prior myocardial iron overload than in control subjects (850.3 ± 115.1 vs 1006.3 ± 35.4, P < .001) and correlated strongly with T2* values (r = 0.874, P < .001). Patients with prior myocardial iron overload had higher ECV than did patients without iron overload (31.3% ± 2.8 vs 28.2% ± 3.4, P = .030) and healthy control subjects (27.0% ± 3.1, P = .003). There was no difference in ECV between patients without iron overload and control subjects (P = .647). ECV correlated with lowest historical T2* (r = -0.469, P = .010) but did not correlate significantly with left ventricular ejection fraction (r = -0.216, P = .252) or global longitudinal strain (r = -0.164, P = .423). Conclusion ECV is significantly increased in thalassemia major and is associated with myocardial iron overload. These abnormalities may potentially reflect diffuse interstitial myocardial fibrosis. (©) RSNA, 2015 Online supplemental material is available for this article.

Rationale and Objectives: To assess the performance of automated quantification of left ventricular function and mass based on heart deformation analysis (HDA) in asymptomatic older adults., Materials and Methods: This study complied with Health Insurance Portability and Accountability Act regulations. Following the approval of the institutional review board, 160 asymptomatic older participants were recruited for cardiac magnetic resonance imaging including two-dimensional cine images covering the entire left ventricle in short-axis view. Data analysis included the calculation of left ventricular ejection fraction (LVEF), left ventricular mass (LVM), and cardiac output (CO) using HDA and standard global cardiac function analysis (delineation of end-systolic and end-diastolic left ventricle epi- and endocardial borders). The agreement between methods was evaluated using intraclass correlation coefficient (ICC) and coefficient of variation (CoV)., Results: HDA had a shorter processing time than the standard method (1.5 ± 0.3 min/case vs. 5.8 ± 1.4 min/case, P < 0.001). There was good agreement for LVEF (ICC = 0.552, CoV = 10.5%), CO (ICC = 0.773, CoV = 13.5%), and LVM (ICC = 0.859, CoV = 14.5%) acquired with the standard method and HDA. There was a systemic bias toward lower LVEF (62.8% ± 8.3% vs. 69.3% ± 6.7%, P < 0.001) and CO (4.4 ± 1.0 L/min vs. 4.8 ± 1.3 L/min, P < 0.001) by HDA compared to the standard technique. Conversely, HDA overestimated LVM (114.8 ± 30.1 g vs. 100.2 ± 29.0 g, P < 0.001) as compared to the reference method., Conclusions: HDA has the potential to measure LVEF, CO, and LVM without the need for user interaction based on standard cardiac two-dimensional cine images., (Copyright © 2015 The Association of University Radiologists. Published by Elsevier Inc. All rights reserved.)

Background: Measurement of myocardial T2* is becoming widely used in the assessment of patients at risk for cardiac iron overload. The conventional breath-hold, ECG-triggered, segmented, multi-echo gradient echo (MGRE) sequence used for myocardial T2* quantification is very sensitive to respiratory motion and may not be feasible in patients who are unable to breath-hold. We propose a free-breathing myocardial T2* mapping approach that combines a single-shot gradient-echo echo-planar imaging (GRE-EPI) sequence for T2*-weighted image acquisition with automatic non-rigid motion correction (MOCO) of respiratory motion between single-shot images., Methods: ECG-triggered T2*-weighted images at different echo times were acquired by a black-blood, single-shot GRE-EPI sequence during free-breathing. A single image at a single TE is acquired in each heartbeat. Automatic non-rigid MOCO was applied to correct for in-plane respiratory motion before pixel-wise T2* mapping. In a total of 117 patients referred for clinical cardiac magnetic resonance exams, the free-breathing MOCO GRE-EPI sequence was compared to the breath-hold segmented MGRE approach. Image quality was scored independently by 2 experienced observers blinded to the particular image acquisition strategy. T2* measurements in the interventricular septum and in the liver were compared for the two methods in all cases with adequate image quality., Results: T2* maps were acquired in all 117 patients using the breath-hold MGRE and the free-breathing MOCO GRE-EPI approaches, including 8 patients with myocardial iron overload and 25 patients with hepatic iron overload. The mean image quality of the free-breathing MOCO GRE-EPI images was scored significantly higher than that of the breath-hold MGRE images by both reviewers. Out of the 117 studies, 21 breath-hold MGRE studies (17.9% of all the patients) were scored to be less than adequate or very poor by both reviewers, while only 2 free-breathing MOCO GRE-EPI studies were scored to be less than adequate image quality. In a comparative evaluation of the images with at least adequate quality, the intra-class correlation coefficients for myocardial and liver T2* were 0.868 and 0.986 respectively (p < 0.001), indicating that the T2* measured by breath-hold MGRE and free-breathing MOCO GRE-EPI were in close agreement. The coefficient of variation between the breath-hold and free-breathing approaches for myocardial and liver T2* were 9.88% and 9.38% respectively. Bland-Altman plots demonstrated good absolute agreement of T2* in the interventricular septum and the liver from the free-breathing and breath-hold approaches (mean differences -0.03 and 0.16 ms, respectively)., Conclusion: The free-breathing approach described for T2* mapping using MOCO GRE-EPI enables accurate myocardial and liver T2* measurements and is insensitive to respiratory motion.

A collaborative framework was initiated to establish a community resource of ground truth segmentations from cardiac MRI. Multi-site, multi-vendor cardiac MRI datasets comprising 95 patients (73 men, 22 women; mean age 62.73±11.24years) with coronary artery disease and prior myocardial infarction, were randomly selected from data made available by the Cardiac Atlas Project (Fonseca et al., 2011). Three semi- and two fully-automated raters segmented the left ventricular myocardium from short-axis cardiac MR images as part of a challenge introduced at the STACOM 2011 MICCAI workshop (Suinesiaputra et al., 2012). Consensus myocardium images were generated based on the Expectation-Maximization principle implemented by the STAPLE algorithm (Warfield et al., 2004). The mean sensitivity, specificity, positive predictive and negative predictive values ranged between 0.63 and 0.85, 0.60 and 0.98, 0.56 and 0.94, and 0.83 and 0.92, respectively, against the STAPLE consensus. Spatial and temporal agreement varied in different amounts for each rater. STAPLE produced high quality consensus images if the region of interest was limited to the area of discrepancy between raters. To maintain the quality of the consensus, an objective measure based on the candidate automated rater performance distribution is proposed. The consensus segmentation based on a combination of manual and automated raters were more consistent than any particular rater, even those with manual input. The consensus is expected to improve with the addition of new automated contributions. This resource is open for future contributions, and is available as a test bed for the evaluation of new segmentation algorithms, through the Cardiac Atlas Project (www.cardiacatlas.org)., (Copyright © 2013 Elsevier B.V. All rights reserved.)

The assessment of myocardial fibrosis and extracellular volume requires accurate estimation of myocardial T1 s. While image acquisition using the modified Look-Locker inversion recovery technique is clinically feasible for myocardial T1 mapping, respiratory motion can limit its applicability. Moreover, the conventional T1 fitting approach using the magnitude inversion recovery images can lead to less stable T1 estimates and increased computational cost. In this article, we propose a novel T1 mapping scheme that is based on phase-sensitive image reconstruction and the restoration of polarity of the MR signal after inversion. The motion correction is achieved by registering the reconstructed images after background phase removal. The restored signal polarity of the inversion recovery signal helps the T1 fitting resulting in improved quality of the T1 map and reducing the computational cost. Quantitative validation on a data cohort of 45 patients proves the robustness of the proposed method against varying image contrast. Compared to the magnitude T1 fitting, the proposed phase-sensitive method leads to less fluctuation in T1 estimates., (Copyright © 2012 Wiley Periodicals, Inc.)

Quantification of myocardial T1 relaxation has potential value in the diagnosis of both ischemic and nonischemic cardiomyopathies. Image acquisition using the modified Look-Locker inversion recovery technique is clinically feasible for T1 mapping. However, respiratory motion limits its applicability and degrades the accuracy of T1 estimation. The robust registration of acquired inversion recovery images is particularly challenging due to the large changes in image contrast, especially for those images acquired near the signal null point of the inversion recovery and other inversion times for which there is little tissue contrast. In this article, we propose a novel motion correction algorithm. This approach is based on estimating synthetic images presenting contrast changes similar to the acquired images. The estimation of synthetic images is formulated as a variational energy minimization problem. Validation on a consecutive patient data cohort shows that this strategy can perform robust nonrigid registration to align inversion recovery images experiencing significant motion and lead to suppression of motion induced artifacts in the T1 map., (Copyright © 2011 Wiley-Liss, Inc.)

Patient motion is a major limitation for magnetic resonance imaging. Recent theoretical advances incorporate explicit rigid and non-rigid motion compensation into conventional image reconstruction for multi-shot acquisitions and recover motion-free images by solving a general matrix inversion problem. Although the theory has been established, applications are rare due to the challenges of estimating motion field for every pixel of every shot. In this paper we propose a method to overcome this difficulty using the inverse-consistent deformable registration supplying both forward and backward deformations for matrix inversion. We further extend this framework for multi-coil motion compensated image reconstruction using the eigen-mode analysis. Both simulations and in vivo studies demonstrate the effectiveness of our approach.

Conventional cardiac MRI acquisition involves a multi-step approach, requiring a few double-oblique localizers in order to locate the heart and prescribe long- and short-axis views of the heart. This approach is operator-dependent and time-consuming. We propose a new approach to automating and accelerating the acquisition process to improve the clinical workflow. We capture a highly accelerated static 3D full-chest volume through parallel imaging within one breath-hold. The left ventricle is localized and segmented, including left ventricle outflow tract. A number of cardiac landmarks are then detected to anchor the cardiac chambers and calculate standard 2-, 3-, and 4-chamber long-axis views along with a short-axis stack. Learning-based algorithms are applied to anatomy segmentation and anchor detection. The proposed algorithm is evaluated on 173 localizer acquisitions. The entire view planning is fully automatic and takes less than 10 seconds in our experiments.

Cardiac magnetic resonance imaging (MRI) has advanced to become a powerful diagnostic tool in clinical practice. Robust and fast cardiac modeling is important for structural and functional analysis of the heart. Cardiac anchors provide strong cues to extract morphological and functional features for diagnosis and disease monitoring. We present a fully automatic method and system that is able to detect these cues. The proposed approach explores expert knowledge embedded in a large annotated database. Exemplar cues in our experiments include left ventricle (LV) base plane and LV apex from long-axis images, and right ventricle (RV) insertion points from short-axis images. We evaluate the proposed approach on 8304 long-axis images from 188 patients and 891 short-axis images from 338 patients that are acquired from different vendors. In addition, another evaluation is conducted on an independent 7140 images from 87 patient studies. Experimental results show promise of the proposed approach.

This paper describes a system to automatically segment the left ventricle in all slices and all phases of cardiac cine magnetic resonance datasets. After localizing the left ventricle blood pool using motion, thresholding and clustering, slices are segmented sequentially. For each slice, deformable registration is used to align all the phases, candidates contours are recovered in the average image using shortest paths, and a minimal surface is built to generate the final contours. The advantage of our method is that the resulting contours follow the edges in each phase and are consistent over time. We demonstrate using 19 patient examples that the results are very good. The RMS distance between ground truth and our segmentation is only 1.6 pixels (2.7 mm) and the Dice coefficient is 0.89.

Registration and modeling of shapes are two important problems in computer vision and pattern recognition. Despite enormous progress made over the past decade, these problems are still open. In this paper, we advance the state of the art in both directions. First we consider an efficient registration method that aims to recover a one-to-one correspondence between shapes and introduce measures of uncertainties driven from the data which explain the local support of the recovered transformations. To this end, a free form deformation is used to describe the deformation model. The transformation is combined with an objective function defined in the space of implicit functions used to represent shapes. Once the registration parameters have been recovered, we introduce a novel technique for model building and statistical interpretation of the training examples based on a variable bandwidth kernel approach. The support on the kernels varies spatially and is determined according to the uncertainties of the registration process. Such a technique introduces the ability to account for potential registration errors in the model. Hand-written character recognition and knowledge-based object extraction in medical images are examples of applications that demonstrate the potentials of the proposed framework.

We present a method for automatic localization and rough segmentation of the left ventricle blood pool in cardiac cine magnetic resonance images. The method first detects the whole heart using time-based Fourier analysis. It then segments the left ventricle blood pool by grouping connected components across slices using isoperimetric clustering. The system was tested on 253 datasets and failed in only 2 cases.

Graph-based algorithms have become increasingly popular for medical image segmentation. The fundamental process for each of these algorithms is to use the image content to generate a set of weights for the graph and then set conditions for an optimal partition of the graph with respect to these weights. To date, the heuristics used for generating the weighted graphs from image intensities have largely been ignored, while the primary focus of attention has been on the details of providing the partitioning conditions. In this paper we empirically study the effects of graph connectivity and weighting function on the quality of the segmentation results. To control for algorithm-specific effects, we employ both the Graph Cuts and Random Walker algorithms in our experiments.

In this paper, we present a new segmentation evaluation method that can simulate radiologist's subjective assessment of 3D tumor segmentation in CT images. The method uses a new metric defined as a linear combination of a set of commonly used objective metrics. The weighing parameters of the linear combination are determined by maximizing the rank correlation between radiologist's subjective rating and objective measurements. Experimental results on 93 lesions demonstrate that the new composite metric shows better performance in segmentation evaluation than each individual objective metric. Also, segmentation rating using the composite metric compares well with radiologist's subjective evaluation. Our method has the potential to facilitate the development of new tumor segmentation algorithms and assist large scale segmentation evaluation studies.

This paper presents a new segmentation algorithm which combines active shape model and robust point matching techniques. It can use any simple feature detector to extract a large number of feature points in the image. Robust point matching is then used to search for the correspondences between feature and model points while the model is being deformed along the modes of variation of the active shape model. Although the algorithm is generic, it is particularly suited for medical imaging applications where prior knowledge is available. The value of the proposed method is examined with two different medical imaging modalities (Ultrasound, MRI) and in both 2D and 3D. The experiments have shown that the proposed algorithm is immune to missing feature points and noise. It has demonstrated significant improvements when compared to RPM-TPS and ASM alone.