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Echo-planar time resolved imaging (EPTI) is an effective approach for acquiring high-quality distortion-free images with a multi-shot EPI (ms-EPI) readout. As with traditional ms-EPI acquisitions, inter-shot phase variations present a main challenge when incorporating EPTI into a diffusion-prepared pulse sequence. The aim of this study is to develop a self-navigated Cartesian EPTI-based (scEPTI) acquisition together with a magnitude and phase constrained reconstruction for distortion-free diffusion imaging. A self-navigated Cartesian EPTI-based diffusion-prepared pulse sequence is designed. The different phase components in EPTI diffusion signal are analyzed and an approach to synthesize a fully phase-matched navigator for the inter-shot phase correction is demonstrated. Lastly, EPTI contains richer magnitude and phase information than conventional ms-EPI, such as the magnitude and phase correlations along the temporal dimension. The potential of these magnitude and phase correlations to enhance the reconstruction is explored. The reconstruction results with and without phase matching and with and without phase or magnitude constraints are compared. Compared with reconstruction without phase matching, the proposed phase matching method can improve the accuracy of inter-shot phase correction and reduce signal corruption in the final diffusion images. Magnitude constraints further improve image quality by suppressing the background noise and thereby increasing SNR, while phase constraints can mitigate possible image blurring from adding magnitude constraints. The high-quality distortion-free diffusion images and simultaneous diffusion-relaxometry imaging capacity provided by the proposed EPTI design represent a highly valuable tool for both clinical and neuroscientific assessments of tissue microstructure.

OBJECTIVE. To compare the diagnostic performance of a conventional metal artifact suppression sequence MAVRIC-SL (multi-acquisition variable-resonance image combination selective) and a novel 2.6-fold faster sequence employing robust principal component analysis (RPCA), in the MR evaluation of hip implants at 3T. MATERIALS AND METHODS. 36 total hip implants in 25 patients were scanned at 3T using a conventional MAVRIC-SL proton density-weighted sequence and an RPCA MAVRIC-SL proton density-weighted sequence. Comparison was made of image quality, geometric distortion, visualization around acetabular and femoral components, and conspicuity of abnormal imaging findings using the Wilcoxon signed-rank test and a non-inferiority test. Abnormal findings were correlated with subsequent clinical management and intraoperative findings if the patient underwent subsequent surgery. RESULTS. Mean scores for conventional MAVRIC-SL were better than RPCA MAVRIC-SL for all qualitative parameters (p < 0.05), although the probability of RPCA MAVRIC-SL being clinically useful was non-inferior to conventional MAVRIC-SL (within our accepted 10% difference, p < 0.05), except for visualization around the acetabular component. Abnormal imaging findings were seen in 25 hips, and either equally visible or visible but less conspicuous on RPCA MAVRIC-SL in 21 out of 25 cases. In 4 cases a small joint effusion was queried on MAVRIC-SL but not RPCA MAVRIC-SL, but the presence or absence of a small effusion did not affect subsequent clinical management and patient outcome. CONCLUSION. While overall image quality is reduced, RPCA MAVRIC-SL allows for significantly reduced scan time and maintains almost equal diagnostic performance.

Diffusion weighted Fast Spin Echo (DW-FSE) is a promising approach for distortionless DW imaging that is robust to system imperfections such as eddy currents and off-resonance. Due to non-Carr-Purcell-Meiboom-Gill (CPMG) magnetization, most DW-FSE sequences discard a large fraction of the signal (A joint multishot reconstruction is derived from the non-CPMG signal model. Multishot quadratic phase increment DW-FSE was tested in a standardized diffusion phantom and compared to single-shot DW-FSE and DW-EPI in vivo in the brain, cervical spine, and prostate. The pseudo multiple replica technique was applied to generate g-factor and SNR maps.The proposed joint shot reconstruction eliminates ghosting from shot-to-shot phase and intrashot oscillations. g-factor performance is improved compared to previously proposed reconstructions, permitting efficient multishot imaging. apparent diffusion coefficient estimates in phantom experiments and in vivo are comparable to those obtained with conventional methods.Multi-shot non-CPMG DW-FSE data with full signal can be jointly reconstructed using a linear model.

Magnetic resonance fingerprinting (MRF) is a rapidly developing approach for fast quantitative MRI. A typical drawback of dictionary-based MRF is an explosion of the dictionary size as a function of the number of reconstructed parameters, according to the "curse of dimensionality", which determines an explosion of resource requirements. Neural networks (NNs) have been proposed as a feasible alternative, but this approach is still in its infancy. In this work, we design a deep learning approach to MRF using a fully connected network (FCN). In the first part we investigate, by means of simulations, how the NN performance scales with the number of parameters to be retrieved in comparison with the standard dictionary approach. Four MRF sequences were considered: IR-FISP, bSSFP, IR-FISP-B1 , and IR-bSSFP-B1 , the latter two designed to be more specific for B+1 parameter encoding. Estimation accuracy, memory usage, and computational time required to perform the estimation task were considered to compare the scalability capabilities of the dictionary-based and the NN approaches. In the second part we study optimal training procedures by including different data augmentation and preprocessing strategies during training to achieve better accuracy and robustness to noise and undersampling artifacts. The study is conducted using the IR-FISP MRF sequence exploiting both simulations and in vivo acquisitions. Results demonstrate that the NN approach outperforms the dictionary-based approach in terms of scalability capabilities. Results also allow us to heuristically determine the optimal training strategy to make an FCN able to predict T1 , T2 , and M0 maps that are in good agreement with those obtained with the original dictionary approach. k-SVD denoising is proposed and found to be critical as a preprocessing step to handle undersampled data.

Purpose To investigate a computationally efficient method for optimizing the Cramer-Rao Lower Bound (CRLB) of quantitative sequences without using approximations or an analytical expression of the signal. Methods Automatic differentiation was applied to Bloch simulations and used to optimize several quantitative sequences without the need for approximations or an analytical expression. The results were validated with in vivo measurements and comparisons to prior art. Multi-echo spin echo and DESPO T 1 were used as benchmarks to verify the CRLB implementation. The CRLB of the Magnetic Resonance Fingerprinting (MRF) sequence, which has a complicated analytical formulation, was also optimized using automatic differentiation. Results The sequence parameters obtained for multi-echo spin echo and DESPO T 1 matched results obtained using conventional methods. In vivo, MRF scans demonstrate that the CRLB optimization obtained with automatic differentiation can improve performance in presence of white noise. For MRF, the CRLB optimization converges in 1.1 CPU hours for N TR = 400 and has O ( N TR ) asymptotic runtime scaling for the calculation of the CRLB objective and gradient. Conclusions Automatic differentiation can be used to optimize the CRLB of quantitative sequences without using approximations or analytical expressions. For MRF, the runtime is computationally efficient and can be used to investigate confounding factors as well as MRF sequences with a greater number of repetitions.

Little experimental evidence exists regarding corrective television advertising as a remedy for misleading direct-to-consumer prescription drug ads. We examined how exposure to an ad for a fictitious prescription drug that appeared to offer benefits and risks superior to normative standards for asthma medication (i.e., a simulated violative ad) and a corresponding corrective ad shaped viewer perceptions, understanding, and intended behavior. Through an experiment with 1,057 participants, we found that a corrective ad counteracted viewer belief of an overstatement of efficacy claim, but was less successful in counteracting omission of risk. Corrective ad exposure also affected general viewer perceptions of, and intended behaviors toward, the drug

Background Prescription drug television advertisements containing potentially consequential misinformation sometimes appear in the United States. When that happens, the U.S. Food and Drug Administration can request that companies distribute corrective advertisements to address misinformation and inaccurate claims. Previous research has demonstrated effectiveness in corrective advertising for various products. Objectives The present article builds on that work with a randomized experimental study (n = 6454) of corrective advertising investigating the extent to which visual similarity matters between violative and corrective ads and the extent to which time delay matters between violative and corrective advertisement exposure. Methods Our study sample included overweight or obese U.S. adults recruited from an existing online consumer panel representative of the U.S. adult population. We created a brand for a fictitious prescription weight-loss drug and produced corresponding direct-to-consumer (DTC) television ads. All participants viewed the same violative ad, but were randomly assigned to view corrective ads with different levels of visual similarity and exposure time delay using a 4 × 4 between-subjects factorial design. Results Results suggest corrective ad exposure can influence consumer perceptions of drug efficacy, risks, and benefits previously established by violative ads that overstated drug efficacy, broadened drug indication, and omitted important risk information. Corrective ads also can weaken consumer intentions to consider and investigate a drug. However, ad similarity does not appear to affect consumer perceptions and preferences. Although we found that the effects of violative ad exposure tend to diminish over time, the length of the delay between violative and corrective ad exposure has limited influence. An exception to this was observed with regard to recall of drug benefits and risks, where the impact of corrective ad exposure increases with greater time delay. Conclusions These results extend previous research to a new health condition and hold implications for regulatory policy.

Solid-state potassium-39 NMR spectra of two potassium complexes of crown-ether-based organic ligands (1-KI and 2) have been acquired at 11.75 and 21.1 T and interpreted to provide information on the 39 K quadrupolar and chemical shift tensors. The analyses reveal a large potassium chemical shift tensor span of 75 ± 20 ppm for 1·KI. This appears to be the first such measurement for potassium in an organic complex, thereby suggesting the utility of potassium chemical shift tensors for characterizing organic and biomolecular K+ binding environments. Compound 2 exhibits a cation-π interaction between K + and a phenyl group, and therefore, the 39 K NMR tensors obtained for this compound must be partly representative of this interaction. Analyses of potassium-39 spin-rotation data for gaseous 39 K 19 F and 39 K 35 Cl available from molecular beam experiments performed by Cederberg and co-workers reveal the largest potassium CS tensor spans known to date, 84.39 and 141 ppm, respectively. Collectively, the results obtained highlight the potential of ultrahigh-field potassium-39 solid-state NMR spectroscopy and, in particular, the wide range of the anisotropy of the potassium CS tensor when organic and diatomic systems are considered.

Insulin and insulinlike growth factors I and II (IGF-I and IGF-II) influence mesodermal cell proliferation and differentiation. As multiple growth factors are involved in hemopoietic cell proliferation and differentiation, we assessed the receptor binding and mitogenic effects of these peptides on a panel of mesodermally derived human myeloid leukemic cell lines. The promyelocytic cell line HL60 had the highest level of specific binding for these 125I-labeled ligands, with lower binding to the less differentiated myeloblast cell line KG1 and undifferentiated blast variants of these cell lines (HL60blast, KG1a). Insulin binding affinity and receptor numbers were reduced significantly by chemically induced granulocytic differentiation of HL60 cells and was unchanged following induced monocytic differentiation. No substantial alteration in IGF-I or -II binding occurred with induced HL60 cell differentiation. Insulin and IGF-I demonstrated cross competition for receptor binding and down-regulated their homologous receptors without detectable cross modulation of the heterologous receptors on HL60 cells. IGF-I and insulin increased HL60 cell proliferation, as assessed by 3H-thymidine uptake, IGF-I greater than insulin. IGF-I binding and mitogenic effects were blocked by the monoclonal anti-IGF-I receptor antibody IR3, indicating that IGF-I-induced proliferative effects were mediated via its homologous receptor. In contrast, insulin binding and mitogenesis displayed blocking by both anti-IGI-I and anti-insulin receptor antibodies, indicating mediation of its activity through both receptors. These data demonstrate specific binding and mitogenic interactions between insulin, IGFs, and hemopoietic cells which are associated with their state of differentiation.