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.

Concomitant magnetic-field compensation for 2D spiral-ring turbo spin-echo imaging at 0.55T and 1.5T.

PURPOSE: To develop 2D turbo spin-echo (TSE) imaging using annular spiral rings (abbreviated "SPRING-RIO TSE") with compensation of concomitant gradient fields and B0 inhomogeneity at both 0.55T and 1.5T for fast T2 -weighted imaging. METHODS: Strategies of gradient waveform modifications were implemented in SPRING-RIO TSE for compensation of self-squared concomitant gradient terms at the TE and across echo spacings, along with reconstruction-based corrections to simultaneously compensate for the residual concomitant gradient and B0 field induced phase accruals along the readout. The signal pathway disturbance caused by time-varying and spatially dependent concomitant fields was simulated, and echo-to-echo phase variations before and after sequence-based compensation were compared. Images from SPRING-RIO TSE with no compensation, with compensation, and Cartesian TSE were also compared via phantom and in vivo acquisitions. RESULTS: Simulation showed how concomitant fields affected the signal evolution with no compensation, and both simulation and phantom studies demonstrated the performance of the proposed sequence modifications, as well as the readout off-resonance corrections. Volunteer data showed that after full correction, the SPRING-RIO TSE sequence achieved high image quality with improved SNR efficiency (15%-20% increase), and reduced RF SAR (˜50% reduction), compared to the standard Cartesian TSE, presenting potential benefits, especially in regaining SNR at low-field (0.55T). CONCLUSION: Implementation of SPRING-RIO TSE with concomitant field compensation was tested at 0.55T and 1.5T. The compensation principles can be extended to correct for other trajectory types that are time-varying along the echo train and temporally asymmetric in TSE-based imaging.

Highly accelerated dynamic acquisition of 3D grid-tagged hyperpolarized-gas lung images using compressed sensing.

PURPOSE: To develop and test compressed sensing-based multiframe 3D MRI of grid-tagged hyperpolarized gas in the lung. THEORY AND METHODS: Applying grid-tagging RF pulses to inhaled hyperpolarized gas results in images in which signal intensity is predictably and sparsely distributed. In the present work, this phenomenon was used to produce a sampling pattern in which k-space is undersampled by a factor of approximately seven, yet regions of high k-space energy remain densely sampled. Three healthy subjects received multiframe 3D 3 He tagging MRI using this undersampling method. Images were collected during a single exhalation at eight timepoints spanning the breathing cycle from end-of-inhalation to end-of-exhalation. Grid-tagged images were used to generate 3D displacement maps of the lung during exhalation, and time-resolved maps of principal strains and fractional volume change were generated from these displacement maps using finite-element analysis. RESULTS: Tags remained clearly resolvable for 4-6 timepoints (5-8 s) in each subject. Displacement maps revealed noteworthy temporal and spatial nonlinearities in lung motion during exhalation. Compressive normal strains occurred along all three principal directions but were primarily oriented in the head-foot direction. Fractional volume changes displayed clear bilateral symmetry, but with the lower lobes displaying slightly higher change than the upper lobes in 2 of the 3 subjects. CONCLUSION: We developed a compressed sensing-based method for multiframe 3D MRI of grid-tagged hyperpolarized gas in the lung during exhalation. This method successfully overcomes previous challenges for 3D dynamic grid-tagging, allowing time-resolved biomechanical readouts of lung function to be generated.

Alirocumab and plaque volume, calf muscle blood flow, and walking performance in peripheral artery disease: A randomized clinical trial.

BACKGROUND: The distal superficial femoral artery (SFA) is most commonly affected in peripheral artery disease (PAD). The effects of the proprotein convertase subtilisin/kexin type 9 (PCSK9) inhibitor alirocumab added to statin therapy on SFA atherosclerosis, downstream flow, and walking performance are unknown. METHODS: Thirty-five patients with PAD on maximally tolerated statin therapy were recruited. Patients were randomized to alirocumab 150 mg subcutaneously (n = 18) or matching placebo (n = 17) therapy every 2 weeks for 1 year. The primary outcome was change in SFA plaque volume by black blood magnetic resonance imaging (MRI). Secondary outcomes were changes in calf muscle perfusion by cuff/occlusion hyperemia arterial spin labeling MRI, 6-minute walk distance (6MWD), low-density lipoprotein (LDL) cholesterol, and other biomarkers. RESULTS: Age (mean ± SD) was 64 ± 8 years, 20 (57%) patients were women, 17 (49%) were Black individuals, LDL was 107 ± 36 mg/dL, and the ankle-brachial index 0.71 ± 0.20. The LDL fell more with alirocumab than placebo (mean [95% CI]) (-49.8 [-66.1 to -33.6] vs -7.7 [-19.7 to 4.3] mg/dL; p < 0.0001). Changes in SFA plaque volume and calf perfusion showed no difference between groups when adjusted for baseline (+0.25 [-0.29 to 0.79] vs -0.04 [-0.47 to 0.38] cm3; p = 0.37 and 0.22 [-8.67 to 9.11] vs 3.81 [-1.45 to 9.08] mL/min/100 g; p = 0.46, respectively), nor did 6MWD. CONCLUSION: In this exploratory study, the addition of alirocumab therapy to statins did not alter SFA plaque volume, calf perfusion or 6MWD despite significant LDL lowering. Larger studies with longer follow up that include plaque characterization may improve understanding of the effects of intensive LDL-lowering therapy in PAD (ClinicalTrials.gov Identifier: NCT02959047).

Improving biomarker testing in advanced non-small-cell lung cancer and metastatic colorectal cancer: experience from a large community oncology network in the USA.

Aim: Biomarker testing detects actionable driver mutations to inform first-line treatment in advanced non-small-cell lung cancer (aNSCLC) and metastatic colorectal cancer (mCRC). This study evaluated biomarker testing in a nationwide database (NAT) versus the OneOncology (OneOnc) community network. Patients & methods: Patients with aNSCLC or mCRC with ≥1 biomarker test in a de-identified electronic health record-derived database were evaluated. OneOnc oncologists were surveyed. Results: Biomarker testing rates were high and comparable between OneOnc and NAT; next-generation sequencing (NGS) rates were higher at OneOnc. Patients with NGS versus other biomarker testing were more likely to receive targeted treatment. Operational challenges and insufficient tissue were barriers to NGS testing. Conclusion: Community cancer centers delivered personalized healthcare through biomarker testing.

What is this article about? Cancer therapies often work better in certain subgroups of patients. Tumors may have characteristics that can predict which therapies may be more likely to work. These cancer biomarkers may be identified by special testing, such as next-generation sequencing (NGS). If a biomarker is detected, the patient can potentially be treated with medicine that targets that biomarker. This study looked at biomarker testing of lung and colon cancers in two community cancer practices (OneOncology [OneOnc] and nationwide database [NAT]). What were the results? The biomarker testing rates were high (≥81%) and similar between OneOnc and NAT. NGS testing rates were higher at OneOnc than at NAT (58 vs 49% for non-small-cell lung cancer, 55 vs 42% for metastatic colorectal cancer [mCRC]), suggesting the success of OneOnc's networkwide educational, pathway and operational programs. NGS testing was lower in community practices due to operational challenges and insufficient tissue collection. Patients who had NGS versus other biomarker testing were more likely to receive treatment specifically for that biomarker. However, some patients started treatment before their biomarker results were reported, usually because of their disease and a long wait time for biomarker test results. What do the results of the study mean? Community cancer centers can treat patients with targeted medicine based on biomarker testing results. There are opportunities to increase the number of patients getting NGS testing, shorten turnaround times and reduce the number of patients who start treatment before getting their biomarker test results.

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.

Concomitant field compensation of spiral turbo spin-echo at 0.55 T.

OBJECTIVE: Diagnostic-quality neuroimaging methods are vital for widespread clinical adoption of low field MRI. Spiral imaging is an efficient acquisition method that can mitigate the reduced signal-to-noise ratio at lower field strengths. As concomitant field artifacts are worse at lower field, we propose a generalizable quadratic gradient-field nulling as an echo-to-echo compensation and apply it to spiral TSE at 0.55 T. MATERIALS AND METHODS: A spiral in-out TSE acquisition was developed with a compensation for concomitant field variation between spiral interleaves, by adding bipolar gradients around each readout to minimize phase differences at each refocusing pulse. Simulations were performed to characterize concomitant field compensation approaches. We demonstrate our proposed compensation method in phantoms and (n = 8) healthy volunteers at 0.55 T. RESULTS: Spiral read-outs with integrated spoiling demonstrated strong concomitant field artifacts but were mitigated using the echo-to-echo compensation. Simulations predicted a decrease of concomitant field phase RMSE between echoes of 42% using the proposed compensation. Spiral TSE improved SNR by 17.2 ± 2.3% compared to reference Cartesian acquisition. DISCUSSION: We demonstrated a generalizable approach to mitigate concomitant field artifacts for spiral TSE acquisitions via the addition of quadratic-nulling gradients, which can potentially improve neuroimaging at low-field through increased acquisition efficiency.

SPRING-RIO TSE: 2D T2 -Weighted Turbo Spin-Echo brain imaging using SPiral RINGs with retraced in/out trajectories.

PURPOSE: To develop a new approach to 2D turbo spin -echo (TSE) imaging using annular spiral rings with a retraced in/out trajectory, dubbed "SPRING-RIO TSE", for fast T2 -weighted brain imaging at 3T. METHODS: A long spiral trajectory was split into annular segmentations that were then incorporated into a 2D TSE acquisition module to fully exploit the sampling efficiency of spiral rings. A retraced in/out trajectory strategy coupled with spiral-ring TSE was introduced to increase SNR, mitigate T2 -decay induced artifacts, and self-correct moderate off-resonance while maintaining the target TE and causing no scan time penalty. Model-based k-space estimation and semiautomatic off-resonance correction algorithms were implemented to minimize effects of k-space trajectory infidelity and B0 inhomogeneity, respectively. The resulting SPRING-RIO TSE method was compared to the original spiral-ring (abbreviated "SPRING") TSE and Cartesian TSE using simulations, and phantom and in vivo acquisitions. RESULTS: Simulation and phantom studies demonstrated the performance of the proposed SPRING-RIO TSE pulses sequence, as well as that of trajectory correction and off-resonance correction. Volunteer data showed that the proposed method achieves high-quality 2D T2 -weighted brain imaging with a higher scan efficiency (0:45 min/14 slices versus 1:31 min/14 slices), improved image contrast, and reduced specific absorption rate compared to conventional 2D Cartesian TSE. CONCLUSION: 2D T2 -weighted brain imaging using spiral-ring TSE was implemented and tested, providing several potential advantages over conventional 2D Cartesian TSE imaging.

Associations Between Medicaid Insurance, Biomarker Testing, and Outcomes in Patients With Advanced NSCLC.

BACKGROUND: Evidence suggests that patients with Medicaid experience lower-quality cancer care than those with commercial insurance. Whether this trend persists in the era of personalized medicine is unclear. This study examined the associations between Medicaid (vs commercial) insurance and receipt of biomarker testing, targeted therapy, and overall survival in patients with advanced non-small cell lung cancer (aNSCLC). METHODS: We conducted a retrospective study of patients who received an aNSCLC diagnosis from January 2011 to September 2019 using a nationwide US healthcare database. Eligible patients were aged 18 to 64 years with Medicaid or commercial insurance at diagnosis. Receipt of biomarker testing (ALK, EGFR, ROS1, BRAF, and PD-L1) was assessed. The likelihood of testing, biomarker-driven therapy (cancer immunotherapy or tyrosine kinase inhibitor treatment), and mortality were compared by insurance type using adjusted Cox regression. RESULTS: Our sample included 6,145 commercially insured and 865 Medicaid beneficiaries. Medicaid beneficiaries were more likely to be Black or African American (20% vs 9.3%; P <.001) and were less likely to have undergone biomarker testing (57% vs 71%; P <.001). In the adjusted analysis, Medicaid beneficiaries were less likely to have evidence of testing (hazard ratio [HR], 0.81; P <.001), any first-line treatment (HR, 0.72; P <.001), and first-line biomarker-driven therapy (HR, 0.70; P <.001). Medicaid beneficiaries with evidence of biomarker testing had a lower risk of death compared with those without evidence of biomarker testing (HR, 1.27 [95% CI, 1.06-1.52]; P =.010). Higher risk of death was observed in patients with Medicaid versus commercially insured patients (HR, 1.23; P <.001); this result remained unchanged after adjusting for biomarker testing (HR, 1.22; P < .001) but was partially ameliorated after adjustment for testing and treatment type (HR, 1.12; P =.010). CONCLUSIONS: Medicaid beneficiaries with aNSCLC were less likely to receive biomarker testing and biomarker-driven therapies, which may in part contribute to a higher observed risk of mortality compared with commercially insured patients.

Patients with allergic asthma have lower risk of severe COVID-19 outcomes than patients with nonallergic asthma.

BACKGROUND: Although asthma does not appear to be a risk factor for severe coronavirus disease 2019 (COVID-19), outcomes could vary for patients with different asthma subtypes. The objective of this analysis was to compare COVID-19 outcomes in real-world cohorts in the United States among patients with asthma, with or without evidence of allergy. METHODS: In a retrospective analysis of the COVID-19 Optum electronic health record dataset (February 20, 2020-January 28, 2021), patients diagnosed with COVID-19 with a history of moderate-to-severe asthma were divided into 2 cohorts: those with evidence of allergic asthma and those without (nonallergic asthma). After 1:1 propensity score matching, in which covariates were balanced and potential bias was removed, COVID-19 outcomes were compared between cohorts. RESULTS: From a COVID-19 population of 591,198 patients, 1595 patients with allergic asthma and 8204 patients with nonallergic asthma were identified. After propensity score matching (n = 1578 per cohort), risk of death from any cause after COVID-19 diagnosis was significantly lower for patients with allergic vs nonallergic asthma (hazard ratio, 0.48; 95% CI 0.28-0.83; P = 0.0087), and a smaller proportion of patients with allergic vs nonallergic asthma was hospitalized within - 7 to + 30 days of COVID-19 diagnosis (13.8% [n = 217] vs 18.3% [n = 289]; P = 0.0005). Among hospitalized patients, there were no significant differences between patients with allergic or nonallergic asthma in need for intensive care unit admission, respiratory support, or COVID-19 treatment. CONCLUSIONS: Asthma subtype may influence outcomes after COVID-19; patients with allergic asthma are at lower risk for hospitalization/death than those with nonallergic asthma.

Adenoma Detection Rate (ADR) Irrespective of Indication Is Comparable to Screening ADR: Implications for Quality Monitoring.

BACKGROUND & AIMS: Adenoma detection rate (ADR) is a key measure of colonoscopy quality. However, efficient measurement of ADR can be challenging because many colonoscopies are performed for non-screening purposes. Measuring ADR without being restricted to screening indication may likely facilitate more widespread implementation of quality monitoring. We hypothesized that the ADR for all colonoscopies, irrespective of the indication, would be equivalent to the ADR for screening colonoscopies. METHODS: We reviewed consecutive colonoscopies at two Veterans Affairs centers performed by 21 endoscopists over 6 months in 2015. We calculated the ADR for screening exams, non-screening (surveillance and diagnostic) exams, and all exams (irrespective of indication), correcting for within-endoscopist correlation. We then performed simulation modeling to calculate the ADRs under 16 hypothetical scenarios of various indication distributions. We simulated 100,000 trials with 3,000 participants, randomly assigned indication (screening, surveillance, diagnostic, and FIT+) from a multinomial distribution, randomly drew adenoma using the observed ADRs per indication, and calculated 95% confidence intervals of the mean differences in ADR of screening and non-screening indications. RESULTS: Among 2628 colonoscopies performed by 21 gastroenterologists, the indication was screening in 28.9%, surveillance in 48.2% and diagnostic in 22.9%. There was no significant difference in the ADR, 50% (95%CI: 45-56%) for all colonoscopies vs 49% (95%CI: 43-56%) for screening exams (p=.55). ADRs were 56% for surveillance and 38% for diagnostic exams. In our simulation modeling, only one out of 16 scenarios (screening 10%, surveillance 70%, diagnostic 10% and FIT+ 10%) resulted in a significant difference between the calculated ADRs for screening and non-screening indications. CONCLUSIONS: In our study, the overall ADR computed from all colonoscopies was not significantly different than the conventional ADR based on screening colonoscopies. Assessing ADR for colonoscopy irrespective of indication may be adequate for quality monitoring, and could facilitate the implementation of quality measurement and reporting. Future prospective studies should evaluate the validity of using overall ADR for quality reporting in other jurisdictions before adopting this method in clinical practice.

One-minute whole-brain magnetization transfer ratio imaging with intrinsic B1 -correction.

PURPOSE: Magnetization transfer ratio (MTR) histograms are used widely for the assessment of diffuse pathological changes in the brain. For broad clinical application, MTR scans should not only be fast, but confounding factors should also be minimized for high reproducibility. To this end, a 1-minute whole-brain spiral MTR method with intrinsic B1 -field correction is introduced. METHODS: A spiral multislice spoiled gradient-echo sequence with adaptable magnetization-transfer saturation pulses (angle ß) is proposed. After a low-resolution single-shot spiral readout and a dummy preparation period, high-resolution images are acquired using an interleaved spiral readout. For whole-brain MTR imaging, 50 interleaved slices with three different magnetization-transfer contrasts (ß = 0°, 350°, and 550°) together with an intrinsic B1 -field map are recorded in 58.5 seconds on a clinical 3T system. From the three contrasts, two sets of MTR images are derived and used for subsequent B1 correction, assuming a linear dependency on ß. For validation, a binary spin bath model is used. RESULTS: For the proposed B1 -correction scheme, numerical simulations indicate for brain tissue a decrease of about a factor of 10 for the B1 -related bias on MTR. As a result, following B1 correction, MTR differences in gray and white matter become markedly accentuated, and the reproducibility of MTR histograms from scan-rescan experiments is improved. Furthermore, B1 -corrected MTR histograms show a lower variability for age-matched normal-appearing brain tissue. CONCLUSION: From its speed and offering intrinsic B1 correction, the proposed method shows excellent prospects for clinical studies that explore magnetization-transfer effects based on MTR histogram analysis.

Suppression of artifact-generating echoes in cine DENSE using deep learning.

PURPOSE: To use deep learning for suppression of the artifact-generating T1 -relaxation echo in cine displacement encoding with stimulated echoes (DENSE) for the purpose of reducing the scan time. METHODS: A U-Net was trained to suppress the artifact-generating T1 -relaxation echo using complementary phase-cycled data as the ground truth. A data-augmentation method was developed that generates synthetic DENSE images with arbitrary displacement-encoding frequencies to suppress the T1 -relaxation echo modulated for a range of frequencies. The resulting U-Net (DAS-Net) was compared with k-space zero-filling as an alternative method. Non-phase-cycled DENSE images acquired in shorter breath-holds were processed by DAS-Net and compared with DENSE images acquired with phase cycling for the quantification of myocardial strain. RESULTS: The DAS-Net method effectively suppressed the T1 -relaxation echo and its artifacts, and achieved root Mean Square(RMS) error = 5.5 ± 0.8 and structural similarity index = 0.85 ± 0.02 for DENSE images acquired with a displacement encoding frequency of 0.10 cycles/mm. The DAS-Net method outperformed zero-filling (root Mean Square error = 5.8 ± 1.5 vs 13.5 ± 1.5, DAS-Net vs zero-filling, P < .01; and structural similarity index = 0.83 ± 0.04 vs 0.66 ± 0.03, DAS-Net vs zero-filling, P < .01). Strain data for non-phase-cycled DENSE images with DAS-Net showed close agreement with strain from phase-cycled DENSE. CONCLUSION: The DAS-Net method provides an effective alternative approach for suppression of the artifact-generating T1 -relaxation echo in DENSE MRI, enabling a 42% reduction in scan time compared to DENSE with phase-cycling.

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.

A preclinical study of diffusion-weighted MRI contrast as an early indicator of thermal ablation.

PURPOSE: Intraoperative T2 -weighted (T2-w) imaging unreliably captures image contrast specific to thermal ablation after transcranial MR-guided focused ultrasound surgery, impeding dynamic imaging feedback. Using a porcine thalamotomy model, we test the unproven hypothesis that intraoperative DWI can improve dynamic feedback by detecting lesioning within 30 minutes of transcranial MR-guided focused ultrasound surgery. METHODS: Twenty-five thermal lesions were formed in six porcine models using a clinical transcranial MR-guided focused ultrasound surgery system. A novel diffusion-weighted pulse sequence monitored the formation of T2-w and diffusion-weighted lesion contrast after ablation. Using postoperative T2-w contrast to indicate lesioning, apparent intraoperative image contrasts and diffusion coefficients at each lesion site were computed as a function of time after ablation, observed peak temperature, and observed thermal dose. Lesion sizes segmented from imaging and thermometry were compared. Image reviewers estimated the time to emergence of lesion contrast. Intraoperative image contrasts were analyzed using receiver operator curves. RESULTS: On average, the apparent diffusion coefficient at lesioned sites decreased within 5 minutes after ablation relative to control sites. In-plane lesion areas on intraoperative DWI varied from postoperative T2-w MRI and MR thermometry by 9.6±9.7 mm2 and -4.0±7.1 mm2 , respectively. The 0.25, 0.5, and 0.75 quantiles of the earliest times of observed T2-w and diffusion-weighted lesion contrast were 10.7, 21.0, and 27.8 minutes and 3.7, 8.6, and 11.8 minutes, respectively. The T2-w and diffusion-weighted contrasts and apparent diffusion coefficient values produced areas under the receiver operator curve of 0.66, 0.80, and 0.74, respectively. CONCLUSION: Intraoperative DWI can detect MR-guided focused ultrasound surgery lesion formation in the brain within several minutes after treatment.

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.

Fully-automated global and segmental strain analysis of DENSE cardiovascular magnetic resonance using deep learning for segmentation and phase unwrapping.

BACKGROUND: Cardiovascular magnetic resonance (CMR) cine displacement encoding with stimulated echoes (DENSE) measures heart motion by encoding myocardial displacement into the signal phase, facilitating high accuracy and reproducibility of global and segmental myocardial strain and providing benefits in clinical performance. While conventional methods for strain analysis of DENSE images are faster than those for myocardial tagging, they still require manual user assistance. The present study developed and evaluated deep learning methods for fully-automatic DENSE strain analysis. METHODS: Convolutional neural networks (CNNs) were developed and trained to (a) identify the left-ventricular (LV) epicardial and endocardial borders, (b) identify the anterior right-ventricular (RV)-LV insertion point, and (c) perform phase unwrapping. Subsequent conventional automatic steps were employed to compute strain. The networks were trained using 12,415 short-axis DENSE images from 45 healthy subjects and 19 heart disease patients and were tested using 10,510 images from 25 healthy subjects and 19 patients. Each individual CNN was evaluated, and the end-to-end fully-automatic deep learning pipeline was compared to conventional user-assisted DENSE analysis using linear correlation and Bland Altman analysis of circumferential strain. RESULTS: LV myocardial segmentation U-Nets achieved a DICE similarity coefficient of 0.87 ± 0.04, a Hausdorff distance of 2.7 ± 1.0 pixels, and a mean surface distance of 0.41 ± 0.29 pixels in comparison with manual LV myocardial segmentation by an expert. The anterior RV-LV insertion point was detected within 1.38 ± 0.9 pixels compared to manually annotated data. The phase-unwrapping U-Net had similar or lower mean squared error vs. ground-truth data compared to the conventional path-following method for images with typical signal-to-noise ratio (SNR) or low SNR (p < 0.05), respectively. Bland-Altman analyses showed biases of 0.00 ± 0.03 and limits of agreement of - 0.04 to 0.05 or better for deep learning-based fully-automatic global and segmental end-systolic circumferential strain vs. conventional user-assisted methods. CONCLUSIONS: Deep learning enables fully-automatic global and segmental circumferential strain analysis of DENSE CMR providing excellent agreement with conventional user-assisted methods. Deep learning-based automatic strain analysis may facilitate greater clinical use of DENSE for the quantification of global and segmental strain in patients with cardiac disease.

Non-Cartesian slice-GRAPPA and slice-SPIRiT reconstruction methods for multiband spiral cardiac MRI.

PURPOSE: Spiral MRI has advantages for cardiac imaging, and multiband (MB) spiral MRI of the heart shows promise. However, current reconstruction methods for MB spiral imaging have limitations. We sought to develop improved reconstruction methods for MB spiral cardiac MRI. METHODS: Two reconstruction methods were developed. The first is non-Cartesian slice-GRAPPA (NCSG), which uses phase demodulation and gridding operations before application of a Cartesian slice-separating kernel. The second method, slice-SPIRiT, formulates the reconstruction as a minimization problem that enforces in-plane coil consistency and consistency with the acquired MB data, and uses through-plane coil sensitivity information in the iterative solution. These methods were compared with conjugate-gradient SENSE in phantoms and volunteers. Temporal alternation of CAIPIRINHA (controlled aliasing in parallel imaging results in higher acceleration) phase and the use of a temporal filter were also investigated. RESULTS: Phantom experiments with 3 simultaneous slices (MB = 3) showed that mean artifact power was highest for conjugate-gradient SENSE, lower for NCSG, and lowest for slice-SPIRiT. For volunteer cine imaging (MB = 3, N = 5), the artifact power was 0.182 ± 0.037, 0.148 ± 0.036, and 0.139 ± 0.034 for conjugate-gradient SENSE, NCSG, and slice-SPIRiT, respectively (P < .05, analysis of variance). Temporal alternation of CAIPIRINHA reduced artifacts for both NCSG and slice-SPIRiT. CONCLUSION: The NCSG and slice-SPIRiT methods provide more accurate reconstructions for MB spiral cine imaging compared with conjugate-gradient SENSE. These methods hold promise for non-Cartesian MB imaging.

Quantitative Relationships Between Individual Lower-Limb Muscle Volumes and Jump and Sprint Performances of Basketball Players.

Xie, T, Crump, KB, Ni, R, Meyer, CH, Hart, JM, Blemker, SS, and Feng, X. Quantitative relationships between individual lower-limb muscle volumes and jump and sprint performances of basketball players. J Strength Cond Res 34(3): 623-631, 2020-Lower body skeletal muscles play an essential role in athletic performance; however, because of the difficulty in obtaining detailed information of each individual muscle, the quantitative relationships between individual muscle volumes and performance are not well studied. The aim of this study was to accurately measure individual muscle volumes and identify the muscles with strong correlations with jump and sprint performance metrics for basketball players. Ten male varsity basketball players and 8 club players were scanned using magnetic resonance imaging (MRI) and instructed to perform various jump and sprint tests. The volumes of all lower-limb muscles were calculated from MRI and normalized by body surface area to reduce the effect of the body size differences. In analysis, feature selection was first used to identify the most relevant muscles, followed by correlation analysis to quantify the relationships between the selected muscles and each performance metric. Vastus medialis and semimembranosus were found to be the most relevant muscles for jump while adductor longus and vastus medialis were selected for sprint. Strong correlations (r = 0.664-0.909) between the selected muscles and associated performance tests were found for varsity players, and moderate correlations (r = -0.203 to 0.635) were found for club players. One possible application is that for well-trained varsity players, a targeted training scheme focusing on the selected muscles may be an effective method to further improve jump and sprint performances.

Depressive Symptomatology, Racial Discrimination Experience, and Brain Tissue Volumes Observed on Magnetic Resonance Imaging.

Not much is known about brain structural change in younger populations and minorities. The cross-sectional relationship between depressive symptomatology and racial discrimination with structural measures of brain tissue volume was investigated using magnetic resonance images of 710 participants in the Coronary Artery Risk Development in Young Adults CARDIA Study in 2010. Those reporting depressive symptoms and racial discrimination had lower total brain matter volume compared with those who reported neither (-8.8 mL, 95% confidence interval (CI): -16.4, -1.2), those who reported depressive symptoms only (-10.9 mL, 95% CI: -20.4, -1.4), and those who reported racial discrimination only (-8.6 mL, 95% CI: -16.5, -0.8). Results were similar for total normal white matter. There were 103% higher odds (odds ratio = 2.03, 95% CI: 1.32, 3.14) of being in the highest quartile of white matter hyperintensities in those with depressive symptoms only compared to those without. Although tests for interaction by race were not statistically significant, sensitivity analyses stratified by race revealed inverse associations with total brain matter and total white matter volumes only among black participants with combined depressive symptomatology and experience of racial discrimination, and positive associations only among white participants with depressive symptoms with presence of white matter hyperintensities, suggesting future studies may focus on race.