Journal Article

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

Fujita, Nana, Watanabe, Yusuke, Abe, Osamu, Okimoto, Naomasa, Yasaka, Koichiro, Kanzawa, Jun

2024

Overview

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.

• Publisher: Springer Berlin Heidelberg,Springer Nature B.V
• Subject: Algorithms / Brain / Brain Infarction / Computed tomography / Conspicuity / Deep Learning / Diagnostic Neuroradiology / Humans / Image quality / Image reconstruction / Imaging / Iterative methods / Male / Males / Medical imaging / Medicine / Medicine & Public Health / Neuroimaging / Neurology / Neuroradiology / Neurosciences / Neurosurgery / Putamen / Qualitative analysis / Radiation Dosage / Radiographic Image Interpretation, Computer-Assisted / Radiology / Retrospective Studies / Statistical analysis / Substantia alba / Tomography, X-Ray Computed / Ventricle / Ventricles (cerebral)