» Articles » PMID: 28454640

The Advantage of Digital Tomosynthesis for Pulmonary Nodule Detection Concerning Influence of Nodule Location and Size: a Phantom Study

Overview
Journal Clin Radiol
Specialty Radiology
Date 2017 Apr 30
PMID 28454640
Citations 6
Authors
Affiliations
Soon will be listed here.
Abstract

Aim: To investigate the advantage of digital tomosynthesis (DTS) over chest radiography (CXR) and dual-energy subtraction radiography (DES) for pulmonary nodule detection according to the location and size of solid simulated pulmonary nodules (SPNs).

Materials And Methods: Ninety-six SPNs of variable sizes were inserted into eight different regions of a lung phantom. These regions were further classified into two groups of danger and non-danger zones based on anatomical location influencing the detection of pulmonary nodules. The 96 cases with inserted SPNs and an additional nodule-free 96 control cases all underwent CXR, DES, and DTS examinations. Three observers independently reviewed all the images. The jackknife alternative free-response receiver operating characteristic was used to analyse diagnostic performance for each technique.

Results: DTS was superior to CXR and DES for detection of smaller SPNs, except in the retrodiaphragmatic and apical regions. DTS outperformed CXR and DES for detection of larger SPNs in the paramediastinal region. For 5- and 8-mm SPNs, DTS was superior to CXR and DES in the apical, paramediastinal and lateral pulmonary regions. In the retrodiaphragmatic region, the three techniques showed similar diagnostic performance regardless of the SPN size. DES was similar to DTS for detection of 8-mm SPN in the apical region. For 10- and 12-mm SPNs, CXR and DES showed similar diagnostic performance to DTS in the apical and lateral pulmonary regions; however, DTS was superior to CXR and DES in the paramediastinal region.

Conclusions: DTS significantly improved the capability to detect synthetic pulmonary nodules compared with CXR and DES, for detection of smaller nodules in the apical, paramediastinal, and lateral pulmonary regions, and larger nodules located in the paramediastinal region in a thoracic phantom.

Citing Articles

Next-generation digital chest tomosynthesis.

Gange C, Ku J, Gosangi B, Liu J, Maolinbay M J Clin Imaging Sci. 2024; 14:22.

PMID: 38975057 PMC: 11225395. DOI: 10.25259/JCIS_4_2024.


The diagnostic performance and clinical value of deep learning-based nodule detection system concerning influence of location of pulmonary nodule.

You S, Park J, Park B, Shin H, Ha T, Yun J Insights Imaging. 2023; 14(1):149.

PMID: 37726452 PMC: 10509107. DOI: 10.1186/s13244-023-01497-4.


Digital Tomosynthesis as a Problem-Solving Technique to Confirm or Exclude Pulmonary Lesions in Hidden Areas of the Chest.

Baratella E, Quaia E, Crimi F, Minelli P, Cioffi V, Ruaro B Diagnostics (Basel). 2023; 13(6).

PMID: 36980318 PMC: 10046899. DOI: 10.3390/diagnostics13061010.


Evaluate the performance of four artificial intelligence-aided diagnostic systems in identifying and measuring four types of pulmonary nodules.

Wu M, Li Y, Fu B, Wang G, Chu Z, Deng D J Appl Clin Med Phys. 2020; 22(1):318-326.

PMID: 33369008 PMC: 7856495. DOI: 10.1002/acm2.13142.


Digital Tomosynthesis and COVID-19: An Improvement in the Assessment of Pulmonary Opacities.

Calvo I, SantaCruz-Calvo S, Aranzana M, Marmol P, Luque J, Peral I Arch Bronconeumol (Engl Ed). 2020; 56(11):761-763.

PMID: 32994088 PMC: 7365055. DOI: 10.1016/j.arbres.2020.06.017.