Radiomics and visual analysis for predicting success of transplantation of heterotopic glioblastoma in mice with MRI.
J Neurooncol
; 169(2): 257-267, 2024 Sep.
Article
en En
| MEDLINE
| ID: mdl-38960965
ABSTRACT
BACKGROUND:
Quantifying tumor growth and treatment response noninvasively poses a challenge to all experimental tumor models. The aim of our study was, to assess the value of quantitative and visual examination and radiomic feature analysis of high-resolution MR images of heterotopic glioblastoma xenografts in mice to determine tumor cell proliferation (TCP).METHODS:
Human glioblastoma cells were injected subcutaneously into both flanks of immunodeficient mice and followed up on a 3 T MR scanner. Volumes and signal intensities were calculated. Visual assessment of the internal tumor structure was based on a scoring system. Radiomic feature analysis was performed using MaZda software. The results were correlated with histopathology and immunochemistry.RESULTS:
21 tumors in 14 animals were analyzed. The volumes of xenografts with high TCP (H-TCP) increased, whereas those with low TCP (L-TCP) or no TCP (N-TCP) continued to decrease over time (p < 0.05). A low intensity rim (rim sign) on unenhanced T1-weighted images provided the highest diagnostic accuracy at visual analysis for assessing H-TCP (p < 0.05). Applying radiomic feature analysis, wavelet transform parameters were best for distinguishing between H-TCP and L-TCP / N-TCP (p < 0.05).CONCLUSION:
Visual and radiomic feature analysis of the internal structure of heterotopically implanted glioblastomas provide reproducible and quantifiable results to predict the success of transplantation.Palabras clave
Texto completo:
1
Colección:
01-internacional
Banco de datos:
MEDLINE
Asunto principal:
Neoplasias Encefálicas
/
Imagen por Resonancia Magnética
/
Glioblastoma
/
Trasplante de Neoplasias
Límite:
Animals
/
Female
/
Humans
/
Male
Idioma:
En
Revista:
J Neurooncol
Año:
2024
Tipo del documento:
Article
País de afiliación:
Alemania