Quantitative functional imaging of the pigeon brain: implications for the evolution of avian powered flight.

The evolution of flight is a rare event in vertebrate history, and one that demands functional integration across multiple anatomical/physiological systems. The neuroanatomical basis for such integration and the role that brain evolution assumes in behavioural transformations remain poorly understood. We make progress by (i) generating a positron emission tomography (PET)-based map of brain activity for pigeons during rest and flight, (ii) using these maps in a functional analysis of the brain during flight, and (iii) interpreting these data within a macroevolutionary context shaped by non-avian dinosaurs. Although neural activity is generally conserved from rest to flight, we found significant increases in the cerebellum as a whole and optic flow pathways. Conserved activity suggests processing of self-movement and image stabilization are critical when a bird takes to the air, while increased visual and cerebellar activity reflects the importance of integrating multimodal sensory information for flight-related movements. A derived cerebellar capability likely arose at the base of maniraptoran dinosaurs, where volumetric expansion and possible folding directly preceded paravian flight. These data represent an important step toward establishing how the brain of modern birds supports their unique behavioural repertoire and provide novel insights into the neurobiology of the bird-like dinosaurs that first achieved powered flight.

Deep learning-based rapid image reconstruction and motion correction for high-resolution cartesian first-pass myocardial perfusion imaging at 3T.

PURPOSE: To develop and evaluate a deep learning (DL) -based rapid image reconstruction and motion correction technique for high-resolution Cartesian first-pass myocardial perfusion imaging at 3T with whole-heart coverage for both single-slice (SS) and simultaneous multi-slice (SMS) acquisitions. METHODS: 3D physics-driven unrolled network architectures were utilized for the reconstruction of high-resolution Cartesian perfusion imaging. The SS and SMS multiband (MB) = 2 networks were trained from 135 slices from 20 subjects. Structural similarity index (SSIM), peak SNR (PSNR), and normalized RMS error (NRMSE) were assessed, and prospective images were blindly graded by two experienced cardiologists (5, excellent; 1, poor). For respiratory motion correction, a 2D U-Net based motion corrected network was proposed, and the temporal fidelity and second-order derivative were calculated to assess the performance of the motion correction. RESULTS: Excellent performance was demonstrated in the proposed technique with high SSIM and PSNR, and low NRMSE. Image quality scores were (4.3 [4.3, 4.4], 4.5 [4.4, 4.6], 4.3 [4.3, 4.4], and 4.5 [4.3, 4.5]) for SS DL and SS L1-SENSE, MB = 2 DL and MB = 2 SMS-L1-SENSE, respectively, showing no statistically significant difference (p > 0.05 for SS and SMS) between (SMS)-L1-SENSE and the proposed DL technique. The network inference time was around 4 s per dynamic perfusion series with 40 frames while the time of (SMS)-L1-SENSE with GPU acceleration was approximately 30 min. CONCLUSION: The proposed DL-based image reconstruction and motion correction technique enabled rapid and high-quality reconstruction for SS and SMS MB = 2 high-resolution Cartesian first-pass perfusion imaging at 3T.

High-resolution spiral real-time cardiac cine imaging with deep learning-based rapid image reconstruction and quantification.

The objective of the current study was to develop and evaluate a DEep learning-based rapid Spiral Image REconstruction (DESIRE) and deep learning (DL)-based segmentation approach to quantify the left ventricular ejection fraction (LVEF) for high-resolution spiral real-time cine imaging, including 2D balanced steady-state free precession imaging at 1.5 T and gradient echo (GRE) imaging at 1.5 and 3 T. A 3D U-Net-based image reconstruction network and 2D U-Net-based image segmentation network were proposed and evaluated. Low-rank plus sparse (L+S) served as the reference for the image reconstruction network and manual contouring of the left ventricle was the reference of the segmentation network. To assess the image reconstruction quality, structural similarity index, peak signal-to-noise ratio, normalized root-mean-square error, and blind grading by two experienced cardiologists (5: excellent; 1: poor) were performed. To assess the segmentation performance, quantification of the LVEF on GRE imaging at 3 T was compared with the quantification from manual contouring. Excellent performance was demonstrated by the proposed technique. In terms of image quality, there was no difference between L+S and the proposed DESIRE technique. For quantification analysis, the proposed DL method was not different to the manual segmentation method (p > 0.05) in terms of quantification of LVEF. The reconstruction time for DESIRE was ~32 s (including nonuniform fast Fourier transform [NUFFT]) per dynamic series (40 frames), while the reconstruction time of L+S with GPU acceleration was approximately 3 min. The DL segmentation takes less than 5 s. In conclusion, the proposed DL-based image reconstruction and quantification techniques enabled 1-min image reconstruction for the whole heart and quantification with automatic reconstruction and quantification of the left ventricle function for high-resolution spiral real-time cine imaging with excellent performance.

ACR benchmark testing of a novel high-speed ring-gantry linac kV-CBCT system.

A new generation cone-beam computed tomography (CBCT) system with new hardware design and advanced image reconstruction algorithms is available for radiation treatment simulation or adaptive radiotherapy (HyperSight CBCT imaging solution, Varian Medical Systems-a Siemens Healthineers company). This study assesses the CBCT image quality metrics using the criteria routinely used for diagnostic CT scanner accreditation as a first step towards the future use of HyperSight CBCT images for treatment planning and target/organ delineations. Image performance was evaluated using American College of Radiology (ACR) Program accreditation phantom tests for diagnostic computed tomography systems (CTs) and compared HyperSight images with a standard treatment planning diagnostic CT scanner (Siemens SOMATOM Edge) and with existing CBCT systems (Varian TrueBeam version 2.7 and Varian Halcyon version 2.0).  Image quality performance for all Varian HyperSight CBCT vendor-provided imaging protocols were assessed using ACR head and body ring CT phantoms, then compared to existing imaging modalities. Image quality analysis metrics included contrast-to-noise (CNR), spatial resolution, Hounsfield number (HU) accuracy, image scaling, and uniformity. All image quality assessments were made following the recommendations and passing criteria provided by the ACR. The Varian HyperSight CBCT imaging system demonstrated excellent image quality, with the majority of vendor-provided imaging protocols capable of passing all ACR CT accreditation standards. Nearly all (8/11) vendor-provided protocols passed ACR criteria using the ACR head phantom, with the Abdomen Large, Pelvis Large, and H&N vendor-provided protocols produced HU uniformity values slightly exceeding passing criteria but remained within the allowable minor deviation levels (5-7 HU maximum differences). Compared to other existing CT and CBCT imaging modalities, both HyperSight Head and Pelvis imaging protocols matched the performance of the SOMATOM CT scanner, and both the HyperSight and SOMATOM CT substantially surpassed the performance of the Halcyon 2.0 and TrueBeam version 2.7 systems. Varian HyperSight CBCT imaging system could pass almost all tests for all vendor-provided protocols using ACR accreditation criteria, with image quality similar to those produced by diagnostic CT scanners and significantly better than existing linac-based CBCT imaging systems.

Clinical and Echocardiographic Diversity Associated With Physical Fitness in the Project Baseline Health Study: Implications for Heart Failure Staging.

BACKGROUND: Clinical and echocardiographic features may carry diverse information about the development of heart failure (HF). Therefore, we determined heterogeneity in clinical and echocardiographic phenotypes and its association with exercise capacity. METHODS: In 2036 community-dwelling individuals, we defined echocardiographic profiles of left and right heart remodeling and dysfunction. We subdivided the cohort based on presence (+) or absence (-) of HF risk factors (RFs) and echocardiographic abnormalities (RF-/Echo-, RF-/Echo+, RF+/Echo-, RF+/Echo+). Multivariable-adjusted associations between subgroups and physical performance metrics from 6-minute walk and treadmill exercise testing were assessed. RESULTS: The prevalence was 35.3% for RF-/Echo-, 4.7% for RF-/Echo+, 39.3% for RF+/Echo-, and 20.6% for RF+/Echo+. We observed large diversity in echocardiographic profiles in the Echo+ group. Participants with RF-/Echo+ (18.6% of Echo+) had predominantly echocardiographic abnormalities other than left ventricular (LV) diastolic dysfunction, hypertrophy and reduced ejection fraction, whereas their physical performance was similar to RF-/Echo-. In contrast, participants with RF+/Echo+ presented primarily with LV hypertrophy or dysfunction, features that related to lower 6-minute walking distance and lower exercise capacity. CONCLUSIONS: Subclinical echocardiographic abnormalities suggest HF pathogenesis, but the presence of HF risk factors and type of echo abnormality should be considered so as to distinguish adverse from benign adaptation and to stratify HF risk.

Dynamic cardiac MRI with high spatiotemporal resolution using accelerated spiral-out and spiral-in/out bSSFP pulse sequences at 1.5 T.

OBJECTIVE: To develop two spiral-based bSSFP pulse sequences combined with L + S reconstruction for accelerated ungated, free-breathing dynamic cardiac imaging at 1.5 T. MATERIALS AND METHODS: Tiny golden angle rotated spiral-out and spiral-in/out bSSFP sequences combined with view-sharing (VS), compressed sensing (CS), and low-rank plus sparse (L + S) reconstruction were evaluated and compared via simulation and in vivo dynamic cardiac imaging studies. The proposed methods were then validated against the standard cine, in terms of quantitative image assessment and qualitative quality rating. RESULTS: The L + S method yielded the least residual artifacts and the best image sharpness among the three methods. Both spiral cine techniques showed clinically diagnostic images (score > 3). Compared to standard cine, there were significant differences in global image quality and edge sharpness for spiral cine techniques, while there was significant difference in image contrast for the spiral-out cine but no significant difference for the spiral-in/out cine. There was good agreement in left ventricular ejection fraction for both the spiral-out cine (- 1.6 [Formula: see text] 3.1%) and spiral-in/out cine (- 1.5 [Formula: see text] 2.8%) against standard cine. DISCUSSION: Compared to the time-consuming standard cine (~ 5 min) which requires ECG-gating and breath-holds, the proposed spiral bSSFP sequences achieved ungated, free-breathing cardiac movies at a similar spatial (1.5 × 1.5 × 8 mm3) and temporal resolution (36 ms) per slice for whole heart coverage (10-15 slices) within 45 s, suggesting the clinical potential for improved patient comfort or for imaging patients with arrhythmias or who cannot hold their breath.

Defining left ventricular remodeling using lean body mass allometry: a UK Biobank study.

PURPOSE: The geometric patterns of ventricular remodeling are determined using indexed left ventricular mass (LVM), end-diastolic volume (LVEDV) and concentricity, most often measured using the mass-to-volume ratio (MVR). The aims of this study were to validate lean body mass (LBM)-based allometric coefficients for scaling and to determine an index of concentricity that is independent of both volume and LBM. METHODS: Participants from the UK Biobank who underwent both CMR and dual-energy X-ray absorptiometry (DXA) during 2014-2015 were considered (n = 5064). We excluded participants aged ≥ 70 years or those with cardiometabolic risk factors. We determined allometric coefficients for scaling using linear regression of the logarithmically transformed ventricular remodeling parameters. We further defined a multiplicative allometric relationship for LV concentricity (LVC) adjusting for both LVEDV and LBM. RESULTS: A total of 1638 individuals (1057 female) were included. In subjects with lower body fat percentage (< 25% in males, < 35% in females, n = 644), the LBM allometric coefficients for scaling LVM and LVEDV were 0.85 ± 0.06 and 0.85 ± 0.03 respectively (R2 = 0.61 and 0.57, P < 0.001), with no evidence of sex-allometry interaction. While the MVR was independent of LBM, it demonstrated a negative association with LVEDV in (females: r = - 0.44, P < 0.001; males: - 0.38, P < 0.001). In contrast, LVC was independent of both LVEDV and LBM [LVC = LVM/(LVEDV0.40 × LBM0.50)] leading to increased overlap between LV hypertrophy and higher concentricity. CONCLUSIONS: We validated allometric coefficients for LBM-based scaling for CMR indexed parameters relevant for classifying geometric patterns of ventricular remodeling.

Severe acute radiation dermatitis after palbociclib therapy in the setting of palliative radiotherapy.

INTRODUCTION: Cyclin-dependent-kinase 4/6(CDK4/6) inhibitors are widely used as a first-line systemic treatment for patients with hormone receptor-positive, human epidermal growth factor receptor-2 negative metastatic breast cancer. Although many patients with metastatic breast cancer require palliative radiotherapy (RT), there are limited data on the safety of combining a CDK4/6 inhibitor with palliative RT. CASE REPORT: Presented is a case of acute high-grade radiation dermatitis with low-dose palliative RT following administration of palbociclib. A 49-year-old woman with newly diagnosed hormone receptor-positive invasive ductal carcinoma of the left breast presented with lytic bone lesions in the left femur and lumbar spine. The patient initiated treatment with goserelin, tamoxifen, and palbociclib. She underwent prophylactic surgical fixation of the left femur and received post-operative RT encompassing the entire surgical nail (30 Gy/10 fractions) and palliative RT to the lumbar spine for pain relief (20 Gy/5 fractions). During cycle 4, palbociclib was stopped 3 days prior to the start of RT to reduce the risk of toxicity risk. However, 16 days after starting RT, she developed painful erythematous papules and bullae with moist desquamation on the left groin and lumbar spine. MANAGEMENT & OUTCOME: Her symptoms were managed with topical Aquaphor-lidocaine, silver sulfadiazine, and aluminum acetate soaks. Dermatitis subsided to dry desquamation within 2 weeks. The patient denied late toxicity at 11 months follow-up. DISCUSSION: Larger retrospective or prospective studies are needed to further elucidate the safety of combined CDK4/6 inhibitors and RT. In the meantime, special precautions are warranted in patients receiving combined therapy.

Toward Replacing Late Gadolinium Enhancement With Artificial Intelligence Virtual Native Enhancement for Gadolinium-Free Cardiovascular Magnetic Resonance Tissue Characterization in Hypertrophic Cardiomyopathy.

BACKGROUND: Late gadolinium enhancement (LGE) cardiovascular magnetic resonance (CMR) imaging is the gold standard for noninvasive myocardial tissue characterization but requires intravenous contrast agent administration. It is highly desired to develop a contrast agent-free technology to replace LGE for faster and cheaper CMR scans. METHODS: A CMR virtual native enhancement (VNE) imaging technology was developed using artificial intelligence. The deep learning model for generating VNE uses multiple streams of convolutional neural networks to exploit and enhance the existing signals in native T1 maps (pixel-wise maps of tissue T1 relaxation times) and cine imaging of cardiac structure and function, presenting them as LGE-equivalent images. The VNE generator was trained using generative adversarial networks. This technology was first developed on CMR datasets from the multicenter Hypertrophic Cardiomyopathy Registry, using hypertrophic cardiomyopathy as an exemplar. The datasets were randomized into 2 independent groups for deep learning training and testing. The test data of VNE and LGE were scored and contoured by experienced human operators to assess image quality, visuospatial agreement, and myocardial lesion burden quantification. Image quality was compared using a nonparametric Wilcoxon test. Intra- and interobserver agreement was analyzed using intraclass correlation coefficients (ICC). Lesion quantification by VNE and LGE were compared using linear regression and ICC. RESULTS: A total of 1348 hypertrophic cardiomyopathy patients provided 4093 triplets of matched T1 maps, cines, and LGE datasets. After randomization and data quality control, 2695 datasets were used for VNE method development and 345 were used for independent testing. VNE had significantly better image quality than LGE, as assessed by 4 operators (n=345 datasets; P<0.001 [Wilcoxon test]). VNE revealed lesions characteristic of hypertrophic cardiomyopathy in high visuospatial agreement with LGE. In 121 patients (n=326 datasets), VNE correlated with LGE in detecting and quantifying both hyperintensity myocardial lesions (r=0.77-0.79; ICC=0.77-0.87; P<0.001) and intermediate-intensity lesions (r=0.70-0.76; ICC=0.82-0.85; P<0.001). The native CMR images (cine plus T1 map) required for VNE can be acquired within 15 minutes and producing a VNE image takes less than 1 second. CONCLUSIONS: VNE is a new CMR technology that resembles conventional LGE but without the need for contrast administration. VNE achieved high agreement with LGE in the distribution and quantification of lesions, with significantly better image quality.

Free-breathing self-gated continuous-IR spiral T1 mapping: Comparison of dual flip-angle and Bloch-Siegert B1-corrected techniques.

PURPOSE: To develop a B1-corrrected single flip-angle continuous acquisition strategy with free-breathing and cardiac self-gating for spiral T1 mapping, and compare it to a previous dual flip-angle technique. METHODS: Data were continuously acquired using a spiral-out trajectory, rotated by the golden angle in time. During the first 2 s, off-resonance Fermi RF pulses were applied to generate a Bloch-Siegert shift B1 map, and the subsequent data were acquired with an inversion RF pulse applied every 4 s to create a T1* map. The final T1 map was generated from the B1 and the T1* maps by using a look-up table that accounted for slice profile effects, yielding more accurate T1 values. T1 values were compared to those from inversion recovery (IR) spin echo (phantom only), MOLLI, SAturation-recovery single-SHot Acquisition (SASHA), and previously proposed dual flip-angle results. This strategy was evaluated in a phantom and 25 human subjects. RESULTS: The proposed technique showed good agreement with IR spin-echo results in the phantom experiment. For in-vivo studies, the proposed technique and the previously proposed dual flip-angle method were more similar to SASHA results than to MOLLI results. CONCLUSIONS: B1-corrected single flip-angle T1 mapping successfully acquired B1 and T1 maps in a free-breathing, continuous-IR spiral acquisition, providing a method with improved accuracy to measure T1 using a continuous Look-Locker acquisition, as compared to the previously proposed dual excitation flip-angle technique.

A Slice-Low-Rank Plus Sparse (slice-L + S) Reconstruction Method for k-t Undersampled Multiband First-Pass Myocardial Perfusion MRI.

PURPOSE: The synergistic use of k-t undersampling and multiband (MB) imaging has the potential to provide extended slice coverage and high spatial resolution for first-pass perfusion MRI. The low-rank plus sparse (L + S) model has shown excellent performance for accelerating single-band (SB) perfusion MRI. METHODS: A MB data consistency method employing ESPIRiT maps and through-plane coil information was developed. This data consistency method was combined with the temporal L + S constraint to form the slice-L + S method. Slice-L + S was compared to SB L + S and the sequential operations of split slice-GRAPPA and SB L + S (seq-SG-L + S) using synthetic data formed from multislice SB images. Prospectively k-t undersampled MB data were also acquired and reconstructed using seq-SG-L + S and slice-L + S. RESULTS: Using synthetic data with total acceleration rates of 6-12, slice-L + S outperformed SB L + S and seq-SG-L + S (N = 7 subjects) with respect to normalized RMSE and the structural similarity index (P < 0.05 for both). For the specific case with MB factor = 3 and rate 3 undersampling, or for SB imaging with rate 9 undersampling (N = 7 subjects), the normalized RMSE values were 0.037 ± 0.007, 0.042 ± 0.005, and 0.031 ± 0.004; and the structural similarity index values were 0.88 ± 0.03, 0.85 ± 0.03, and 0.89 ± 0.02 for SB L + S, seq-SG-L + S, and slice-L + S, respectively (P < 0.05 for both). For prospectively undersampled MB data, slice-L + S provided better image quality than seq-SG-L + S for rate 6 (N = 7) and rate 9 acceleration (N = 7) as scored by blinded experts. CONCLUSION: Slice-L + S outperformed SB-L + S and seq-SG-L + S and provides 9 slice coverage of the left ventricle with a spatial resolution of 1.5 mm × 1.5 mm with good image quality.

DEep learning-based rapid Spiral Image REconstruction (DESIRE) for high-resolution spiral first-pass myocardial perfusion imaging.

The objective of the current study was to develop and evaluate a DEep learning-based rapid Spiral Image REconstruction (DESIRE) technique for high-resolution spiral first-pass myocardial perfusion imaging with whole-heart coverage, to provide fast and accurate image reconstruction for both single-slice (SS) and simultaneous multislice (SMS) acquisitions. Three-dimensional U-Net-based image enhancement architectures were evaluated for high-resolution spiral perfusion imaging at 3 T. The SS and SMS MB = 2 networks were trained on SS perfusion images from 156 slices from 20 subjects. Structural similarity index (SSIM), peak signal-to-noise ratio (PSNR), and normalized root mean square error (NRMSE) were assessed, and prospective images were blindly graded by two experienced cardiologists (5: excellent; 1: poor). Excellent performance was demonstrated for the proposed technique. For SS, SSIM, PSNR, and NRMSE were 0.977 [0.972, 0.982], 42.113 [40.174, 43.493] dB, and 0.102 [0.080, 0.125], respectively, for the best network. For SMS MB = 2 retrospective data, SSIM, PSNR, and NRMSE were 0.961 [0.950, 0.969], 40.834 [39.619, 42.004] dB, and 0.107 [0.086, 0.133], respectively, for the best network. The image quality scores were 4.5 [4.1, 4.8], 4.5 [4.3, 4.6], 3.5 [3.3, 4], and 3.5 [3.3, 3.8] for SS DESIRE, SS L1-SPIRiT, MB = 2 DESIRE, and MB = 2 SMS-slice-L1-SPIRiT, respectively, showing no statistically significant difference (p = 1 and p = 1 for SS and SMS, respectively) between L1-SPIRiT and the proposed DESIRE technique. The network inference time was ~100 ms per dynamic perfusion series with DESIRE, while the reconstruction time of L1-SPIRiT with GPU acceleration was ~ 30 min. It was concluded that DESIRE enabled fast and high-quality image reconstruction for both SS and SMS MB = 2 whole-heart high-resolution spiral perfusion imaging.

Highlights of the Virtual Society for Cardiovascular Magnetic Resonance 2022 Scientific Conference: CMR: improving cardiovascular care around the world.

The 25th Society for Cardiovascular Magnetic Resonance (SCMR) Annual Scientific Sessions saw 1524 registered participants from more than 50 countries attending the meeting virtually. Supporting the theme "CMR: Improving Cardiovascular Care Around the World", the meeting included 179 invited talks, 52 sessions including 3 plenary sessions, 2 keynote talks, and a total of 93 cases and 416 posters. The sessions were designed so as to showcase the multifaceted role of cardiovascular magnetic resonance (CMR) in identifying and prognosticating various myocardial pathologies. Additionally, various social networking sessions as well as fun activities were organized. The major areas of focus for the future are likely to be rapid efficient and high value CMR exams, automated and quantitative acquisition and post-processing using artificial intelligence and machine learning, multi-contrast imaging and advanced vascular imaging including 4D flow.

Systemic arterial pulsatility index (SAPi) predicts adverse outcomes in advanced heart failure patients.

Ventriculo-arterial (VA) coupling has been shown to have physiologic importance in heart failure (HF). We hypothesized that the systemic arterial pulsatility index (SAPi), a measure that integrates pulse pressure and a proxy for left ventricular end-diastolic pressure, would be associated with adverse outcomes in advanced HF. We evaluated the SAPi ([systemic systolic blood pressure-systemic diastolic blood pressure]/pulmonary artery wedge pressure) obtained from the final hemodynamic measurement in patients randomized to therapy guided by a pulmonary arterial catheter (PAC) and with complete data in the Evaluation Study of Congestive Heart Failure and Pulmonary Artery Catheterization Effectiveness (ESCAPE) trial. Cox proportional hazards regression was performed for the outcomes of (a) death, transplant, left ventricular assist device (DTxLVAD) or hospitalization, (DTxLVADHF) and (b) DTxLVAD. Among 142 patients (mean age 56.8 ± 13.3 years, 30.3% female), the median SAPi was 2.57 (IQR 1.63-3.45). Increasing SAPi was associated with significant reductions in DTxLVAD (HR 0.60 per unit increase in SAPi, 95% CI 0.44-0.84) and DTxLVADHF (HR 0.81 per unit increase, 95% CI 0.70-0.95). Patients with a SAPi ≤ 2.57 had a marked increase in both outcomes, including more than twice the risk of DTxLVAD (HR 2.19, 95% CI 1.11-4.30) over 6 months. Among advanced heart failure patients with invasive hemodynamic monitoring in the ESCAPE trial, SAPi was strongly associated with adverse clinical outcomes. These findings support further investigation of the SAPi to guide treatment and prognosis in HF undergoing invasive hemodynamic monitoring.

Reference change value of global longitudinal strain in clinical practice: A test-rest quality implementation project.

BACKGROUND: Reference change value (RCV) is used to assess the significance of the difference between two measurements after accounting for pre-analytic, analytic, and within-subject variability. The objective of the current study was to define the RCV for global longitudinal strain (GLS) using different semi-automated software in standard clinical practice. METHODS: Using a test-retest study design, we quantified the median coefficient of variation (CV) for GLS using AutoStrain and Automated Cardiac Motion Quantification (aCMQ) by Philips. Triplane left-ventricular ejection fraction (LVEF) was measured for comparison. Multivariable regression analysis was performed to determine factors influencing test-retest CV including image quality and the presence of segmental wall motion abnormalities (WMA). RCV was reported using a standard formula assuming two standard deviations for repeated measurements; results were also translated into Bayesian probability. Total measurement variation was described in terms of its three different components: pre-analytic (acquisition), analytic (measuring variation), and within-subject (biological) variation. RESULT: Of the 44 individuals who were screened, 41 had adequate quality for strain quantification. The mean age of the cohort was 56.4 ± 16.8 years, 41% female, LVEF was 55.8 ± 9.8% and the median and interquartile range for LV GLS was -17.2 [-19.3 to -14.8]%. Autostrain was more time efficient (80% less analysis time) and had a lower total median CV than aCMQ (CV = 7.4% vs. 17.6%, p < .001). The total CV was higher in patients with WMA (6.4% vs. 13.2%, p = .035). In non-segmental disease, the CV translates to a RCV of 15% (corresponding to a probability of real change of 80%). Assuming a within-subject variability of 4.0%, the component analysis identified that inter-reader variability accounts for 3.7% of the CV, while acquisition variability accounts for 4.0%. CONCLUSION: Using test-retest analysis and CVs, we find that an RCV of 15% for GLS represents an optimistic estimate in routine clinical practice. Based on our results, a higher RCV of 17%-21% is needed in order to provide a high probability of clinically meaningful change in GLS in all comers. The methodology presented here for determining measurement reproducibility and RCVs is easily translatable into clinical practice for any imaging parameter.

Dual-excitation flip-angle simultaneous cine and T1 mapping using spiral acquisition with respiratory and cardiac self-gating.

PURPOSE: To develop a free-breathing cardiac self-gated technique that provides cine images and B1+ slice profile-corrected T1 maps from a single acquisition. METHODS: Without breath-holding or electrocardiogram gating, data were acquired continuously on a 3T scanner using a golden-angle gradient-echo spiral pulse sequence, with an inversion RF pulse applied every 4 seconds. Flip angles of 3° and 15° were used for readouts after the first four and second four inversions. Self-gating cardiac triggers were extracted from heart image navigators, and respiratory motion was corrected by rigid registration on each heartbeat. Cine images were reconstructed from the steady-state portion of 15° readouts using a low-rank plus sparse reconstruction. The T1 maps were fit using a projection onto convex sets approach from images reconstructed using slice profile-corrected dictionary learning. This strategy was evaluated in a phantom and 14 human subjects. RESULTS: The self-gated signal demonstrated close agreement with the acquired electrocardiogram signal. The image quality for the proposed cine images and standard clinical balanced SSFP images were 4.31 (±0.50) and 4.65 (±0.30), respectively. The slice profile-corrected T1 values were similar to those of the inversion-recovery spin-echo technique in phantom, and had a higher global T1 value than that of MOLLI in human subjects. CONCLUSIONS: Cine and T1 mapping using spiral acquisition with respiratory and cardiac self-gating successfully acquired T1 maps and cine images in a single acquisition without the need for electrocardiogram gating or breath-holding. This dual-excitation flip-angle approach provides a novel approach for measuring T1 while accounting for B1+ and slice profile effect on the apparent T1∗ .

High spatial resolution spiral first-pass myocardial perfusion imaging with whole-heart coverage at 3 T.

PURPOSE: To develop and evaluate a high spatial resolution (1.25 × 1.25 mm2 ) spiral first-pass myocardial perfusion imaging technique with whole-heart coverage at 3T, to better assess transmural differences in perfusion between the endocardium and epicardium, to quantify the myocardial ischemic burden, and to improve the detection of obstructive coronary artery disease. METHODS: Whole-heart high-resolution spiral perfusion pulse sequences and corresponding motion-compensated reconstruction techniques for both interleaved single-slice (SS) and simultaneous multi-slice (SMS) acquisition with or without outer-volume suppression (OVS) were developed. The proposed techniques were evaluated in 34 healthy volunteers and 8 patients (55 data sets). SS and SMS images were reconstructed using motion-compensated L1-SPIRiT and SMS-Slice-L1-SPIRiT, respectively. Images were blindly graded by 2 experienced cardiologists on a 5-point scale (5, excellent; 1, poor). RESULTS: High-quality perfusion imaging was achieved for both SS and SMS acquisitions with or without OVS. The SS technique without OVS had the highest scores (4.5 [4, 5]), which were greater than scores for SS with OVS (3.5 [3.25, 3.75], P < .05), MB = 2 without OVS (3.75 [3.25, 4], P < .05), and MB = 2 with OVS (3.75 [2.75, 4], P < .05), but significantly higher than those for MB = 3 without OVS (4 [4, 4], P = .95). SMS image quality was improved using SMS-Slice-L1-SPIRiT as compared to SMS-L1-SPIRiT (P < .05 for both reviewers). CONCLUSION: We demonstrated the successful implementation of whole-heart spiral perfusion imaging with high resolution at 3T. Good image quality was achieved, and the SS without OVS showed the best image quality. Evaluation in patients with expected ischemic heart disease is warranted.

Diagnostic Accuracy of Spiral Whole-Heart Quantitative Adenosine Stress Cardiovascular Magnetic Resonance With Motion Compensated L1-SPIRIT.

BACKGROUND: Variable density spiral (VDS) pulse sequences with motion compensated compressed sensing (MCCS) reconstruction allow for whole-heart quantitative assessment of myocardial perfusion but are not clinically validated. PURPOSE: Assess performance of whole-heart VDS quantitative stress perfusion with MCCS to detect obstructive coronary artery disease (CAD). STUDY TYPE: Prospective cross sectional. POPULATION: Twenty-five patients with chest pain and known or suspected CAD and nine normal subjects. FIELD STRENGTH/SEQUENCE: Segmented steady-state free precession (SSFP) sequence, segmented phase sensitive inversion recovery sequence for late gadolinium enhancement (LGE) imaging and VDS sequence at 1.5 T for rest and stress quantitative perfusion at eight short-axis locations. ASSESSMENT: Stenosis was defined as ≥50% by quantitative coronary angiography (QCA). Visual and quantitative analysis of MRI data was compared to QCA. Quantitative analysis assessed average myocardial perfusion reserve (MPR), average stress myocardial blood flow (MBF), and lowest stress MBF of two contiguous myocardial segments. Ischemic burden was measured visually and quantitatively. STATISTICAL TESTS: Student's t-test, McNemar's test, chi-square statistic, linear mixed-effects model, and area under receiver-operating characteristic curve (ROC). RESULTS: Per-patient visual analysis demonstrated a sensitivity of 84% (95% confidence interval [CI], 60%-97%) and specificity of 83% [95% CI, 36%-100%]. There was no significant difference between per-vessel visual and quantitative analysis for sensitivity (69% [95% CI, 51%-84%] vs. 77% [95% CI, 60%-90%], P = 0.39) and specificity (88% [95% CI, 73%-96%] vs. 80% [95% CI, 64%-91%], P = 0.75). Per-vessel quantitative analysis ROC showed no significant difference (P = 0.06) between average MPR (0.68 [95% CI, 0.56-0.81]), average stress MBF (0.74 [95% CI, 0.63-0.86]), and lowest stress MBF (0.79 [95% CI, 0.69-0.90]). Visual and quantitative ischemic burden measurements were comparable (P = 0.85). DATA CONCLUSION: Whole-heart VDS stress perfusion demonstrated good diagnostic accuracy and ischemic burden evaluation. No significant difference was seen between visual and quantitative diagnostic performance and ischemic burden measurements. EVIDENCE LEVEL: 2 TECHNICAL EFFICACY: Stage 2.

Valve-sparing aortic root replacement after neonatal arterial switch operation.

Arterial switch operations (ASO) are lifesaving procedures performed on neonates to treat transposition of the great arteries. However, future operations on the neoaorta may be required due to dilation. We present a case of a 25-year-old female who presented with dilation of her neoaorta and required a David procedure. Her previous ASO resulted in an anterior lie of the pulmonary artery in front of the neoaorta, with both coronary arteries coming off anteriorly. We describe our approach to performing a David procedure on this patient with this unique anatomy.

T2 Relaxation Times at Cardiac MRI in Healthy Adults: A Systematic Review and Meta-Analysis.

Background T2 mapping is an important cardiac MRI technique with applications in various conditions. However, a comprehensive evaluation of the T2 literature for normal values is lacking. Purpose To characterize the ranges of normal values and variability of myocardial T2 relaxation times using a systematic review and meta-analysis of the T2 literature. Materials and Methods PubMed and Cochrane Central were searched from June 2019 to January 2020 for myocardial T2 measurements in healthy adults. Studies quantifying T2 relaxation times conducted at 1.5 T or 3.0 T using gradient and spin-echo (GRASE) or T2-prepared balanced steady-state free precession sequences were included. Summary means were generated using a random-effects model. Subgroup analysis and meta-regression were performed to assess factors causing heterogeneity. Results Of the 2481 articles retrieved, 42 studies were included with 954 healthy adults (mean age, 42.4 years ± 10.5 [standard deviation]; 538 men). The pooled mean of T2 across studies was 52 msec at 1.5 T (95% confidence interval [CI]: 51 msec, 53 msec) and 46 msec at 3.0 T (95% CI: 44 msec, 48 msec) (P ≤ .001). I2 was 98% at 1.5 T and 3.0 T. Meta-regression at 1.5 T and 3.0 T identified vendor (ß at 1.5 T = -4 msec [with Philips as reference], P < .001; ß at 3.0 T = -5 msec, P = .02) and pulse sequence (ß at 1.5 T = -5 msec [with GRASE as reference], P < .001; ß at 3.0 T = -6 msec, P = .002) as significant covariates, but it did not identify any association with covariates of age (ß at 1.5 T = 0 msec per year, P = .70; ß at 3.0 T = 0 msec per year, P = .83) or sex (ß at 1.5 T = -1 msec, P = .88; ß at 3.0 T = 6 msec, P = .42). Conclusion The pooled mean of T2 relaxation times in healthy adults had marked heterogeneity across studies with field strength, vendor, and pulse sequence identified as covariates associated with T2. T2-prepared measurements were similar between vendors at each field strength. © RSNA, 2020 Online supplemental material is available for this article.