Enhanced coronary calcium visualization and detection from dual energy chest x-rays with sliding organ registration.
Comput Med Imaging Graph
; 64: 12-21, 2018 03.
Article
em En
| MEDLINE
| ID: mdl-29397274
ABSTRACT
We have developed a technique to image coronary calcium, an excellent biomarker for atherosclerotic disease, using low cost, low radiation dual energy (DE) chest radiography, with potential for widespread screening from an already ordered exam. Our dual energy coronary calcium (DECC) processing method included automatic heart silhouette segmentation, sliding organ registration and scatter removal to create a bone-image-like, coronary calcium image with significant reduction in motion artifacts and improved calcium conspicuity compared to standard, clinically available DE processing. Experiments with a physical dynamic cardiac phantom showed that DECC processing reduced 73% of misregistration error caused by cardiac motion over a wide range of heart rates and x-ray radiation exposures. Using the functional measurement test (FMT), we determined significant image quality improvement in clinical images with DECC processing (pâ¯<â¯0.0001), where DECC images were chosen best in 94% of human readings. Comparing DECC images to registered and projected CT calcium images, we found good correspondence between the size and location of calcification signals. In a very preliminary coronary calcium ROC study, we used CT Agatston calcium score >50 as the gold standard for an actual positive test result. AUC performance was significantly improved from 0.73⯱â¯0.14 with standard DE to 0.87⯱â¯0.10 with DECC (pâ¯=â¯0.0095) for this limited set of surgical patient data biased towards heavy calcifications. The proposed DECC processing shows good potential for coronary calcium detection in DE chest radiography, giving impetus for a larger clinical evaluation.
Palavras-chave
Texto completo:
1
Coleções:
01-internacional
Base de dados:
MEDLINE
Assunto principal:
Radiografia Torácica
/
Intensificação de Imagem Radiográfica
/
Cálcio
Tipo de estudo:
Diagnostic_studies
Limite:
Humans
Idioma:
En
Revista:
Comput Med Imaging Graph
Assunto da revista:
DIAGNOSTICO POR IMAGEM
Ano de publicação:
2018
Tipo de documento:
Article
País de afiliação:
Estados Unidos