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MRI systems are traditionally engineered to produce close to idealized performance, enabling a simplified pulse sequence design philosophy. An example of this is control of eddy currents produced by gradient fields; usually these are compensated by pre-emphasizing demanded waveforms. This process typically happens invisibly to the pulse designer, allowing them to assume the achieved gradient waveform will be as desired. Whilst convenient, this imposes stricter limits on the sequence design than the hardware can handle (for example, pre-emphasis adds an additional overhead to amplifiers). This strategy can be undesirable particularly for lower performance or resource-limited hardware. Instead we explore the use of a 'digital twin' (i.e. an end-to-end model of the scanner system) to optimize control inputs, resulting in sequences that inherently compensate for known imperfections. We explore digital twin optimization specifically for gradient system imperfections as an exemplar. This is first explored in simulations using a simple exponential eddy current model, then experimentally using an empirical gradient impulse response function on a 7T MRI system. When unconstrained, digital twin optimization reproduces classic pre-emphasis. When strict hardware constraints are imposed (simulating lower performance hardware), it identifies novel sequences for scenarios where classic pre-emphasis would be unachievable. Experimentally, the optimization approach was demonstrated to substantially reduce ghosting effects in echo planar images on a 7T system. Digital twin optimization may allow more efficient use of hardware by taking a whole system approach. Ultimately this could enable the use of cheaper hardware without loss of performance., Comment: 33 pages, 14 figures (including supporting information)

We suggest to utilize the rich information content about microstructural tissue properties entangled in asymmetric balanced steady-state free precession (bSSFP) profiles to estimate multiple diffusion metrics simultaneously by neural network (NN) parameter quantification. A 12-point bSSFP phase-cycling scheme with high-resolution whole-brain coverage is employed at 3 T and 9.4 T for NN input. Low-resolution target diffusion data are derived based on diffusion-weighted spin-echo echo-planar-imaging (SE-EPI) scans, i.e., mean, axial, and radial diffusivity (MD, AD, RD), fractional anisotropy (FA) as well as the spherical coordinates (azimuth ${\Phi}$ and inclination ${\Theta}$) of the principal diffusion eigenvector. A feedforward NN is trained with incorporated probabilistic uncertainty estimation. The NN predictions yielded highly reliable results in white matter (WM) and gray matter (GM) structures for MD. The quantification of FA, AD, and RD was overall in good agreement with the reference but the dependence of these parameters on WM anisotropy was somewhat biased, e.g., in corpus callosum. The inclination ${\Theta}$ was well predicted for anisotropic WM structures while the azimuth ${\Phi}$ was overall poorly predicted. The findings were highly consistent across both field strengths. Application of the optimized NN to high-resolution input data provided whole-brain maps with rich structural details. In conclusion, the proposed NN-driven approach showed potential to provide distortion-free high-resolution whole-brain maps of multiple diffusion metrics at high to ultra-high field strengths in clinically relevant scan times., Comment: 8 Figures, 1 Table. Supporting Information: 2 Supporting Subsections, 1 Supporting Figure

Purpose: A supervised learning framework is proposed to automatically generate MR sequences and corresponding reconstruction based on the target contrast of interest. Combined with a flexible, task-driven cost function this allows for an efficient exploration of novel MR sequence strategies. Methods: The scanning and reconstruction process is simulated end-to-end in terms of RF events, gradient moment events in x and y, and delay times, acting on the input model spin system given in terms of proton density, T1 and T2, and $\Delta$B0. As a proof of concept, we use both conventional MR images and T1 maps as targets and optimize from scratch using the loss defined by data fidelity, SAR penalty, and scan time. Results: In a first attempt, \textit{MRzero} learns gradient and RF events from zero, and is able to generate a target image produced by a conventional gradient echo sequence. Using a neural network within the reconstruction module allows arbitrary targets to be learned successfully. Experiments could be translated to image acquisition at the real system (3T Siemens, PRISMA) and could be verified in the measurements of phantoms and a human brain \textit{in vivo}. Conclusions: Automated MR sequence generation is possible based on differentiable Bloch equation simulations and a supervised learning approach.

This final report describes activities and accomplishments of the Building Friendships project, which developed, implemented, evaluated, and disseminated an intervention to improve the social integration of students with traumatic brain injury (TBI). The project used an ongoing, informal team approach to bring together and mobilize key people in a student's life around the goal of enhancing the student's school- and community-based social network. The project implemented intervention strategies that are both student-centered and environment-centered. These strategies included direct training of students to enhance social skills, training parents in ways to encourage skill generalization, inservice and peer training about TBI, "peer liaisons," facilitation of involvement in school organizations, training staff of community programs, and pairing community volunteers with TBI students. Students, teachers, and family members reported increases in the number of social contacts and overall time spent with nondisabled peers and the average number of reported friends. Individual sections of the report describe the project's context, goals and objectives, conceptual framework, research participants, intervention strategies, logistical problems and modifications, findings, and impact. Extensive appendices include four articles and book chapters resulting from the project, the manual for a video program, and sample newsletter articles. (DB)

This article describes two case studies of children, ages 6 and 8, with severe traumatic brain injuries (TBI) in which direct instruction programs were used to teach a variety of academic skills. Following an initial evaluation, the teacher began individualized instruction 2 to 3 times per week for 6 weeks. After approximately 12 hourly instructional sessions, both students made substantial academic progress in their targeted instructional areas. The gains were seen in both discrete and more complex skills. Both students regained skills lost as a result of their injury and also gained new skills. A table lists learning characteristics of children with TBI and features of the direct instruction approach which address each characteristic. (Contains 13 references.) (DB)

This final report describes the Traumatic Brain Injury (TBI) Home/School Support project, an Oregon project which attempted to decrease stress in parents caring for school-aged children with TBI and to provide support to schools serving students with TBI. During its 3 years of development, the project involved over 50 families of children, ages 5-21, who had experienced a severe traumatic brain injury. In addition, nearly 200 educators throughout Oregon received inservice training and technical assistance. The multi-faceted model on which the project was based included both school-centered and child-centered goals focusing on issues in instructional planning and community participation. The model provided for coordinated family services from the Oregon Head Injury Foundation, a community psychology clinic, a parent-run respite care organization, and a public school-based information and referral program. Results of the project indicated that a combination of coordinated school/home efforts, respite care, case management, and parent training and counseling were of significant assistance to the parents of children with TBI. This report has sections on the project's goals and objectives, conceptual framework, the model and its participants, logistical problems and modifications, findings, impact, and sources of further information. Extensive appendices include articles and book chapters: "A Comparison of Two Psychosocial Interventions for Parents of Children with Acquired Brain Injury: An Exploratory Study" (George H. S. Singer and others); "Comprehensive Family Support for Behavioral Change in Children with Traumatic Brain Injury" (Joseph M. Lucyshyn and others); "Helping Parents Negotiate the School System" (Ann Glang and others); "Tailoring Direct Instruction Techniques for Use with Elementary Students with Brain Injury" (Ann Glang and others); "Training an Interdisciplinary Team in Communication and Decision-Making Skills" (Elizabeth Cooley); "Using Direct Instruction with Brain Injured Students" (Ann Glang and others); and "'You Can't Imagine Unless You've Been There Yourself': A Report on the Concerns of Parents and Children with Acquired Brain Injury" (George H. S. Singer and Charles Nixon). A retreat planning outline, a knowledge quiz, and a teacher questionnaire are also attached. (Contains approximately 190 references.) (DB)