Case-based radiological anatomy instruction using cadaveric MRI imaging and delivered with extended reality web technology.

PURPOSE: Extended reality (XR) technology enhances learning in medical education. The purpose of this study was to develop and apply a case-based approach for teaching radiological anatomy utilizing XR technology for improved student exploration and engagement. METHODS: The workflow consisted of MRI scanning cadavers followed by radiological, pathological, and anatomical assessment, and finally case presentation based on XR visualizations and student interaction. Case information (Subject, History, and Physical Exam) was presented to student groups who generated and recorded hypotheses using Google Forms. RESULTS: Use of all components of the system was voluntary and a total of 74 students responded to the survey request (response rate = 95%). Assessment of the experience was conducted through a qualitative survey comprising four Likert scale questions (1-5, 1 lowest), three binary questions, and open-ended comments. Mean, standard deviation, and overall agreement (mean ± SD, OA) showed that students found MRI scans of cadavers to be helpful for dissections (4.14 ± 1.1, 74.3%) and provided an understanding of relevant anatomy (4.32 ± 0.9, 79.7%), while 78.4% of students used the DICOM viewer to visualize scans of cadavers. The difficulty of use was found to be average (2.90 ± 1.0, 23%). zSpace visualizations were used by 40.5% of students, generally agreeing that an understanding of spatial relationships improved as a result (3.60 ± 1.0, 43.2%). More case-based sessions were favored by 97.3% of students. CONCLUSIONS: Results suggest that cadaveric MRI radiological visualization and XR technology enhance understanding of case-based anatomical dissections and encourage student exploration and engagement.

Improving temporal resolution in fMRI using a 3D spiral acquisition and low rank plus sparse (L+S) reconstruction.

Rapid whole-brain dynamic Magnetic Resonance Imaging (MRI) is of particular interest in Blood Oxygen Level Dependent (BOLD) functional MRI (fMRI). Faster acquisitions with higher temporal sampling of the BOLD time-course provide several advantages including increased sensitivity in detecting functional activation, the possibility of filtering out physiological noise for improving temporal SNR, and freezing out head motion. Generally, faster acquisitions require undersampling of the data which results in aliasing artifacts in the object domain. A recently developed low-rank (L) plus sparse (S) matrix decomposition model (L+S) is one of the methods that has been introduced to reconstruct images from undersampled dynamic MRI data. The L+S approach assumes that the dynamic MRI data, represented as a space-time matrix M, is a linear superposition of L and S components, where L represents highly spatially and temporally correlated elements, such as the image background, while S captures dynamic information that is sparse in an appropriate transform domain. This suggests that L+S might be suited for undersampled task or slow event-related fMRI acquisitions because the periodic nature of the BOLD signal is sparse in the temporal Fourier transform domain and slowly varying low-rank brain background signals, such as physiological noise and drift, will be predominantly low-rank. In this work, as a proof of concept, we exploit the L+S method for accelerating block-design fMRI using a 3D stack of spirals (SoS) acquisition where undersampling is performed in the kz-t domain. We examined the feasibility of the L+S method to accurately separate temporally correlated brain background information in the L component while capturing periodic BOLD signals in the S component. We present results acquired in control human volunteers at 3T for both retrospective and prospectively acquired fMRI data for a visual activation block-design task. We show that a SoS fMRI acquisition with an acceleration of four and L+S reconstruction can achieve a brain coverage of 40 slices at 2mm isotropic resolution and 64 x 64 matrix size every 500ms.

Prefrontal and striatal activation in elderly subjects during concurrent implicit and explicit sequence learning.

Decreased function in the prefrontal cortex (PFC) is regarded as a primary mechanism of cognitive aging. However, despite a strong association between the prefrontal cortex and the neostriatum, the role of the neostriatum in cognitive aging is less certain. In the current study, event-related functional MRI was used to distinguish the cognitive contributions of neostriatal and prefrontal function in elderly versus young subjects. Twenty healthy subjects, 9 elderly (mean age 67.6 years), and 11 young (mean age 22 years) performed a concurrent implicit and explicit sequence learning task while undergoing functional MR imaging. Both groups showed learning in both the implicit and explicit task conditions. Relative to the young subjects, the elderly subjects showed decreased activation in the left PFC during both implicit and explicit learning, decreased activation in the right putamen during implicit learning, and increased activation in the right PFC during explicit learning. Our results support the theory that changes in a network of brain regions, including the dorsolateral prefrontal cortex and the striatum, are related to cognitive aging. Moreover, these changes are observed during an implicit task, and thus do not seem to be mediated by awareness.

Prefrontal functioning during context processing in schizophrenia and major depression: an event-related fMRI study.

Patients with schizophrenia frequently demonstrate hypofrontality in tasks that require executive processing; however questions still remain as to whether prefrontal cortex dysfunctions are specific to schizophrenia, or a general feature of major psychopathology. Context processing is conceptualized as an executive function associated with attention and working memory processes. Impairment in the ability of patients with schizophrenia to represent and maintain context information has been previously reported in a number of studies. To examine the question of the specificity of a context processing deficit to schizophrenia, we used functional MRI and an expectancy AX continuous performance task designed to assess context processing in a group of healthy controls (n=9), depressed patient controls (n=10), and patients with schizophrenia (n=7). The behavioral performance was consistent with a context processing deficit in patients with schizophrenia, but not those with depression. The imaging data replicate previous results in showing abnormal activity in the right middle frontal gyrus (BA9) in schizophrenia patients related to context processing.