Clinical Evaluation of Chest Radiographs Simulated from Helical Computed Tomography.

Clinical Evaluation of Chest Radiographs Simulated from Helical Computed Tomography.

Shields, Allison; Howard, Kateland N; Somasundaram, Shivapriya; Bader, Anna Shlionsky; Gange, Christopher; Haramati, Linda Broyde; Hoerner, Matthew
Academic radiology 2026
1
allison2026clinical

Abstract

This work evaluated the clinical utility and image quality of simulated chest radiographs derived from helical CT scans, compared with a CT localizer and a recent chest radiograph. A cohort of 100 patients were retrospectively evaluated: most chest radiographs (96/100) were acquired on portable units within 24 h of the CT, where only an anterior-posterior view was acquired. The patient table was segmented from each CT dataset and cone-beam projections in the posterior-anterior and lateral orientations were generated, which were then fed into a multi-objective frequency processing (MFP) framework to obtain simulated chest radiographs (sCXR). The sCXR were qualitatively compared to the localizer and radiograph by three radiologists using Likert scale assessments. Friedman and Wilcoxon tests were used to evaluate categorical trends and statistical significance. Image quality was quantitatively evaluated using the presampled modulation transfer function (MTF). The sCXR demonstrated significantly superior image quality when compared to the CT localizer, specifically in the lung region. The tubes/lines/devices category received the lowest ratings across both modalities. At a 30-cm display field of view (DFOV), MFP projections showed an approximate twofold improvement in limiting resolution. The sCXR demonstrated image quality characteristics that were generally comparable to conventional chest radiography in several of the categories under investigation, highlighting the potential of sCXR as a companion image with the added flexibility of generating multiple projection views. Radiologist scoring suggests that additional edge enhancement may be required for high-frequency structures, which experience greater blurring due to table motion and longer exposure times.

Citation

ID: 284709
Ref Key: allison2026clinical
Use this key to autocite in SciMatic or Thesis Manager

References

Blockchain Verification

Account:
NFT Contract Address:
0x95644003c57E6F55A65596E3D9Eac6813e3566dA
Article ID:
284709
Unique Identifier:
10.1016/j.acra.2026.08.053
Network:
Scimatic Chain (ID: 481)
Loading...
Blockchain Readiness Checklist
Authors
Abstract
Journal Name
Year
Title
5/5
Creates 1,000,000 NFT tokens for this article
Token Features:
  • ERC-1155 Standard NFT
  • 1 Million Supply per Article
  • Transferable via MetaMask
  • Permanent Blockchain Record
Blockchain QR Code
Scan with Saymatik Web3.0 Wallet

Saymatik Web3.0 Wallet