Evaluation of the depiction ability of similar subtraction images using digital chest radiographs of different patients.
Radiol Phys Technol
; 12(1): 40-45, 2019 Mar.
Article
in En
| MEDLINE
| ID: mdl-30460476
ABSTRACT
The temporal subtraction (TS) technique requires the same patient's chest radiographs (CXRs) acquired on different dates, whereas the similar subtraction (SS) technique can be used in patients who have no previous CXR, using similar CXRs from different patients. This study aimed to examine the depiction ability of SS images with simulated nodules in comparison with that of TS images with 2- and 7-year acquisition intervals. One hundred patients were randomly selected from our image database. The most recently acquired images of the patients were used as target images for subtraction. The simulated nodule was superimposed on each target image to examine the usefulness of the SS technique. The most (Top 1) and ten most (Top 10) similar images for each target image were identified in the 24,254-image database using a template-matching technique, and used for the SS technique. SS and TS images were obtained using a previously developed nonlinear image-warping technique. The depiction ability of SS and TS images was evaluated using the contrast-to-noise ratio (CNR). The proportion of Top 1 SS images showing higher CNR than that of the TS images with 2- and 7-year acquisition intervals was 28% (28/100) and 33% (33/100), respectively. Moreover, the proportion of cases that had any of the Top 10 SS images with higher CNRs than those of TS images with 2- and 7-year acquisition intervals was 56% (56/100) and 72% (72/100), respectively. Our study indicates that the SS technique can potentially be used to detect lung nodules on CXRs.
Key words
Full text:
1
Collection:
01-internacional
Database:
MEDLINE
Main subject:
Radiography, Thoracic
/
Subtraction Technique
Limits:
Humans
Language:
En
Journal:
Radiol Phys Technol
Journal subject:
BIOFISICA
/
RADIOLOGIA
Year:
2019
Document type:
Article
Affiliation country:
Japan