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.