Applying dynamic contrast-enhanced MRI tracer kinetic models to differentiate benign and malignant soft tissue tumors.
Cancer Imaging
; 24(1): 64, 2024 May 21.
Article
en En
| MEDLINE
| ID: mdl-38773660
ABSTRACT
BACKGROUND:
To explore the potential of different quantitative dynamic contrast-enhanced (qDCE)-MRI tracer kinetic (TK) models and qDCE parameters in discriminating benign from malignant soft tissue tumors (STTs).METHODS:
This research included 92 patients (41females, 51 males; age range 16-86 years, mean age 51.24 years) with STTs. The qDCE parameters (Ktrans, Kep, Ve, Vp, F, PS, MTT and E) for regions of interest of STTs were estimated by using the following TK models Tofts (TOFTS), Extended Tofts (EXTOFTS), adiabatic tissue homogeneity (ATH), conventional compartmental (CC), and distributed parameter (DP). We established a comprehensive model combining the morphologic features, time-signal intensity curve shape, and optimal qDCE parameters. The capacities to identify benign and malignant STTs was evaluated using the area under the curve (AUC), degree of accuracy, and the analysis of the decision curve.RESULTS:
TOFTS-Ktrans, EXTOFTS-Ktrans, EXTOFTS-Vp, CC-Vp and DP-Vp demonstrated good diagnostic performance among the qDCE parameters. Compared with the other TK models, the DP model has a higher AUC and a greater level of accuracy. The comprehensive model (AUC, 0.936, 0.884-0.988) demonstrated superiority in discriminating benign and malignant STTs, outperforming the qDCE models (AUC, 0.899-0.915) and the traditional imaging model (AUC, 0.802, 0.712-0.891) alone.CONCLUSIONS:
Various TK models successfully distinguish benign from malignant STTs. The comprehensive model is a noninvasive approach incorporating morphological imaging aspects and qDCE parameters, and shows significant potential for further development.Palabras clave
Texto completo:
1
Colección:
01-internacional
Asunto principal:
Neoplasias de los Tejidos Blandos
/
Imagen por Resonancia Magnética
/
Medios de Contraste
Límite:
Adolescent
/
Adult
/
Aged
/
Aged80
/
Female
/
Humans
/
Male
/
Middle aged
Idioma:
En
Revista:
Cancer Imaging
/
Cancer imaging
Asunto de la revista:
DIAGNOSTICO POR IMAGEM
/
NEOPLASIAS
Año:
2024
Tipo del documento:
Article
País de afiliación:
China