Investigating the Use of Traveltime and Reflection Tomography for Deep Learning-Based Sound-Speed Estimation in Ultrasound Computed Tomography.

Ultrasound computed tomography (USCT) quantifies acoustic tissue properties such as the speed-of-sound (SOS). Although full-waveform inversion (FWI) is an effective method for accurate SOS reconstruction, it can be computationally challenging for large-scale problems. Deep learning-based image-to-image learned reconstruction (IILR) methods can offer computationally efficient alternatives. This study investigates the impact of the chosen input modalities on IILR methods for high-resolution SOS reconstruction in USCT. The selected modalities are traveltime tomography (TT) and reflection tomography (RT), which produce a low-resolution SOS map and a reflectivity map, respectively. These modalities have been chosen for their lower computational cost relative to FWI and their capacity to provide complementary information: TT offers a direct SOS measure, while RT reveals tissue boundary information. Systematic analyses were facilitated by employing a virtual USCT imaging system with anatomically realistic numerical breast phantoms. Within this testbed, a supervised convolutional neural network (CNN) was trained to map dual-channel (TT and RT images) to a high-resolution SOS map. Single-input CNNs were trained separately using inputs from each modality alone (TT or RT) for comparison. The accuracy of the methods was systematically assessed using normalized root mean squared error (NRMSE), structural similarity index measure (SSIM), and peak signal-to-noise ratio (PSNR). For tumor detection performance, receiver operating characteristic analysis was employed. The dual-channel IILR method was also tested on clinical human breast data. Ensemble average of the NRMSE, SSIM, and PSNR evaluated on this clinical dataset were 0.2355, 0.8845, and 28.33 dB, respectively.

[Imaging of Sequestered Lumbar Discs]. / 요추 분리추간판의 영상 소견.

Intervertebral disc herniation is frequently encountered in radiological practice. Sequestered disc herniation occurs when the disc material undergoes degeneration and completely loses continuity with the parent nucleus pulposus. Sequestered discs can reside within and outside the spinal canal, exerting a mass effect on adjacent structures, compressing nerve pathways, and eliciting a range of clinical symptoms. In particular, sequestered discs within the dura cannot be identified without durotomy. Therefore, precise preoperative localization is crucial for surgical planning. On MRI, the signal intensity of the sequestered disc may vary due to independent degeneration processes. Additionally, most sequestered disc fragments show varying degrees of peripheral enhancement depending on the degree of angiogenesis and granulation around the isolated tissue. In this article, we review various imaging findings and the location of the sequestered disc to provide patients with an accurate diagnosis and appropriate treatment direction.

Track-Density Ratio Mapping With Fiber Types in the Cerebral Cortex Using Diffusion-Weighted MRI.

The nerve fibers are divided into three categories: projection, commissural, and association fibers. This study demonstrated a novel cortical mapping method based on these three fiber categories using MR tractography data. The MR fiber-track data were extracted using the diffusion-weighted 3T-MRI data from 19 individuals' Human Connectome Project dataset. Anatomical MR images in each dataset were parcellated using FreeSurfer software and Brainnetome atlas. The 5 million extracted tracks per subject by MRtrix software were classified based on the basic cortical structure (cortical area in the left and right hemisphere, subcortical area), after the tracks validation procedure. The number of terminals for each categorized track per unit-sized cortical area (1 mm3) was defined as the track-density in that cortical area. Track-density ratio mapping with fiber types was achieved by mapping the density-dependent color intensity for each categorized tracks with a different primary color. The mapping results showed a highly localized, unique density ratio map determined by fiber types. Furthermore, the quantitative group data analysis based on the parcellation information revealed that the majority of nerve fibers in the brain are association fibers, particularly in temporal, inferior parietal, and occipital lobes, while the projection and commissural fibers were mainly located in the superior part of the brain. Hemispheric asymmetries in the fiber density were also observed, such as long association fiber in the Broca's and Wernicke's areas. We believe this new dimensional brain mapping information allows us to further understand brain anatomy, function.

Proposal for human visual pathway in the extrastriate cortex by fiber tracking method using diffusion-weighted MRI.

The extrastriate cortex in the human visual cortex is divided into two distinct clusters: the "what-information" processing area and the "where-information" processing area. It is widely accepted that the "what-information" cluster is processed through the ventral stream to the temporal cortex, and the "where-information" cluster through the dorsal stream to the parietal cortex. In human neuroanatomy, fiber bundles for the ventral stream (such as the inferior longitudinal fasciculus) are well defined, whereas fibers for the dorsal stream are poorly understood. In this study, we attempted to trace the dorsal stream fibers using a fiber tracking method using 7.0T diffusion-weighted MRI. We used data from a healthy male subject as well as from an unbiasedly selected nine-subject dataset in the Human Connectome Project. The surface of the visual area, including V1, V2, V3, V4, MT, was determined from the Brainnetome atlas (Fan et al., 2016), which is the connectivity-based parcellation framework of the human brain. The resulting visual pathway indicated that the putative pathway for the classical dorsal stream is unlikely to exist. Instead, we demonstrated that fiber connections exist between the angular gyrus with MT in the visual cortex, and between the angular gyrus and IT in the temporal cortex. Through that, we composed a two-pathway model for where-information processing that passes through the angular gyrus. Finally, we proposed a modified human visual pathway model based on our fiber tracking results in this report. The modified where-information pathway will provide a new aspect for the study of human visual processing.