Optimization of a secondary VOI protocol for lung imaging in a clinical CT scanner.
J Appl Clin Med Phys
; 19(4): 271-280, 2018 Jul.
Article
en En
| MEDLINE
| ID: mdl-29785839
ABSTRACT
We present a solution to meet an unmet clinical need of an in-situ "close look" at a pulmonary nodule or at the margins of a pulmonary cyst revealed by a primary (screening) chest CT while the patient is still in the scanner. We first evaluated options available on current whole-body CT scanners for high resolution screening scans, including ROI reconstruction of the primary scan data and HRCT, but found them to have insufficient SNR in lung tissue or discontinuous slice coverage. Within the capabilities of current clinical CT systems, we opted for the solution of a secondary, volume-of-interest (VOI) protocol where the radiation dose is focused into a short-beam axial scan at the z position of interest, combined with a small-FOV reconstruction at the xy position of interest. The objective of this work was to design a VOI protocol that is optimized for targeted lung imaging in a clinical whole-body CT system. Using a chest phantom containing a lung-mimicking foam insert with a simulated cyst, we identified the appropriate scan mode and optimized both the scan and recon parameters. The VOI protocol yielded 3.2 times the texture amplitude-to-noise ratio in the lung-mimicking foam when compared to the standard chest CT, and 8.4 times the texture difference between the lung mimicking and reference foams. It improved details of the wall of the simulated cyst and better resolution in a line-pair insert. The Effective Dose of the secondary VOI protocol was 42% on average and up to 100% in the worst-case scenario of VOI positioning relative to the standard chest CT. The optimized protocol will be used to obtain detailed CT textures of pulmonary lesions, which are biomarkers for the type and stage of lung diseases.
Palabras clave
Texto completo:
1
Colección:
01-internacional
Banco de datos:
MEDLINE
Asunto principal:
Interpretación de Imagen Radiográfica Asistida por Computador
Tipo de estudio:
Guideline
/
Prognostic_studies
Límite:
Humans
Idioma:
En
Revista:
J Appl Clin Med Phys
Asunto de la revista:
BIOFISICA
Año:
2018
Tipo del documento:
Article
País de afiliación:
Estados Unidos