Novel noise reduction filter for improving visibility of early computed tomography signs of hyperacute stroke: evaluation of the filter's performance—preliminary clinical experience

Deep learning reconstruction for improving the visualization of acute brain infarct on computed tomography

PURPOSE

This study aimed to investigate the impact of deep learning reconstruction (DLR) on acute infarct depiction compared with hybrid iterative reconstruction (Hybrid IR).

METHODS

This retrospective study included 29 (75.8 ± 13.2 years, 20 males) and 26 (64.4 ± 12.4 years, 18 males) patients with and without acute infarction, respectively. Unenhanced head CT images were reconstructed with DLR and Hybrid IR. In qualitative analyses, three readers evaluated the conspicuity of lesions based on five regions and image quality. A radiologist placed regions of interest on the lateral ventricle, putamen, and white matter in quantitative analyses, and the standard deviation of CT attenuation (i.e., quantitative image noise) was recorded.

RESULTS

Conspicuity of acute infarct in DLR was superior to that in Hybrid IR, and a statistically significant difference was observed for two readers (p ≤ 0.038). Conspicuity of acute infarct with time from onset to CT imaging at < 24 h in DLR was significantly improved compared with Hybrid IR for all readers (p ≤ 0.020). Image noise in DLR was significantly reduced compared with Hybrid IR with both the qualitative and quantitative analyses (p < 0.001 for all).

CONCLUSION

DLR in head CT helped improve acute infarct depiction, especially those with time from onset to CT imaging at < 24 h.

Synchronized imaging and acoustic analysis of the upper airway in patients with sleep-disordered breathing

Progressive narrowing of the upper airway increases airflow resistance and can produce snoring sounds and apnea/hypopnea events associated with sleep-disordered breathing due to airway collapse. Recent studies have shown that acoustic properties during snoring can be altered with anatomic changes at the site of obstruction. To evaluate the instantaneous association between acoustic features of snoring and the anatomic sites of obstruction, a novel method was developed and applied in nine patients to extract the snoring sounds during sleep while performing dynamic magnetic resonance imaging (MRI). The degree of airway narrowing during the snoring events was then quantified by the collapse index (ratio of airway diameter preceding and during the events) and correlated with the synchronized acoustic features. A total of 201 snoring events (102 pure retropalatal and 99 combined retropalatal and retroglossal events) were recorded, and the collapse index as well as the soft tissue vibration time were significantly different between pure retropalatal (collapse index, 2 ± 11%; vibration time, 0.2 ± 0.3 s) and combined (retropalatal and retroglossal) snores (collapse index, 13 ± 7% [P ≤ 0.0001]; vibration time, 1.2 ± 0.7 s [P ≤ 0.0001]). The synchronized dynamic MRI and acoustic recordings successfully characterized the sites of obstruction and established the dynamic relationship between the anatomic site of obstruction and snoring acoustics.

Usefulness of z-score mapping for quantification of extent of hypoattenuation regions of hyperacute stroke in unenhanced computed tomography: analysis of radiologists' performance

OBJECTIVE

The purpose of this study was to evaluate the usefulness of z-score mapping method on neuroradiologists' performance in quantification of the extent of hypoattenuation regions of hyperacute stroke on unenhanced computed tomographic (CT) images by using the Alberta Stroke Programme Early CT Score system.

METHODS

Twenty-one patients with infarction (<3 hours) were retrospectively selected. Five neuroradiologists interpreted CT images first without and then with z-score maps by using the Alberta Stroke Programme Early CT Score system. Their performances in the quantification of the extent of hypoattenuation were compared.

RESULTS

Average accuracies for the quantification without and with the z-score maps were 82.6% and 86.6%, respectively (P < 0.0001). The average area under the receiver operating characteristic curve for detection of focal hypoattenuation significantly increased from 0.883 to 0.925 (P = 0.01) by use of z-score maps.

CONCLUSIONS

The use of z-score mapping method has the potential to help neuroradiologists quantify the extent of hypoattenuation regions of hyperacute stroke on unenhanced CT images.

Z-score mapping method for extracting hypoattenuation areas of hyperacute stroke in unenhanced CT

RATIONALE AND OBJECTIVES

The purpose of this study was to develop a z-score mapping method on the basis of a voxel-by-voxel analysis to visualize hypoattenuation areas of hyperacute stroke on unenhanced computed tomographic (CT) images.

MATERIALS AND METHODS

The algorithm of the developed method consisted of five main steps: anatomic standardization, the construction of a normal reference database, calculation of the z scores, the elimination of false-positive areas, and the extraction of hypoattenuation areas. The obtained z-score map was then superimposed on the original CT images for identifying hypoattenuation areas of hyperacute stroke on the unenhanced CT images. The method was applied to 21 patients with infarctions of the middle cerebral artery territory <3 hours after symptom onset. The performance of the method was evaluated using receiver-operating characteristic analysis.

RESULTS

Hypoattenuation regions could be significantly distinguished from normal regions by z-score values (P < .0001). The area under the receiver-operating characteristic curve for distinction between 68 hypoattenuation regions and 142 normal regions was 0.834.

CONCLUSIONS

The developed method has the potential to accurately indicate high-signal intensity areas corresponding to hypoattenuation areas on CT images in the hyperacute stage of stroke.