Subacute Tension Hemopneumothorax with Novel Electrocardiogram Findings

This case report describes a patient with a subacute right-sided tension hemopneumothorax following an occult stab. The patient’s electrocardiogram (ECG), performed as part of a standardized triage process, demonstrated significant abnormalities that misguided initial resuscitation, but resolved following evacuation of the tension hemopneumothorax. Tension pneumothorax is typically regarded as an immediately life-threatening condition that requires emergent management with needle or tube thoracostomy. However, we believe that subacute tension pneumothorax may be a rarely observed clinical phenomenon and may lead to unique ECG findings. We believe that the ECG changes we observed provided an early clue to the eventual diagnosis of a subacute tension pneumothorax and have not been previously described in this setting.

Magnetic resonance fingerprinting review part 2: Technique and directions

Peer Reviewedhttps://deepblue.lib.umich.edu/bitstream/2027.42/154317/1/jmri26877.pdfhttps://deepblue.lib.umich.edu/bitstream/2027.42/154317/2/jmri26877_am.pd

Self-calibrated subspace reconstruction for multidimensional MR fingerprinting for simultaneous relaxation and diffusion quantification

Purpose To propose a new reconstruction method for multidimensional MR fingerprinting (mdMRF) to address shading artifacts caused by physiological motion-induced measurement errors without navigating or gating. Methods The proposed method comprises two procedures: self-calibration and subspace reconstruction. The first procedure (self-calibration) applies temporally local matrix completion to reconstruct low-resolution images from a subset of under-sampled data extracted from the k-space center. The second procedure (subspace reconstruction) utilizes temporally global subspace reconstruction with pre-estimated temporal subspace from low-resolution images to reconstruct aliasing-free, high-resolution, and time-resolved images. After reconstruction, a customized outlier detection algorithm was employed to automatically detect and remove images corrupted by measurement errors. Feasibility, robustness, and scan efficiency were evaluated through in vivo human brain imaging experiments. Results The proposed method successfully reconstructed aliasing-free, high-resolution, and time-resolved images, where the measurement errors were accurately represented. The corrupted images were automatically and robustly detected and removed. Artifact-free T1, T2, and ADC maps were generated simultaneously. The proposed reconstruction method demonstrated robustness across different scanners, parameter settings, and subjects. A high scan efficiency of less than 20 s per slice has been achieved. Conclusion The proposed reconstruction method can effectively alleviate shading artifacts caused by physiological motion-induced measurement errors. It enables simultaneous and artifact-free quantification of T1, T2, and ADC using mdMRF scans without prospective gating, with robustness and high scan efficiency