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18F-fluorodeoxyglucose (18F-FDG) positron emission tomography/computed tomography (PET/CT) imaging of pediatric neuroblastoma: a multi-omics parameters method to predict MYCN copy number category.
Qian, Luo-Dan; Zhou, Zi-Ang; Li, Si-Qi; Liu, Jun; Zhang, Shu-Xin; Ren, Jia-Liang; Wang, Wei; Yang, Jigang.
Afiliación
  • Qian LD; Department of Radiology, Beijing Friendship Hospital, Capital Medical University, Beijing, China.
  • Zhou ZA; Nuclear Medicine Department, Beijing Friendship Hospital, Capital Medical University, Beijing, China.
  • Li SQ; Nuclear Medicine Department, Beijing Friendship Hospital, Capital Medical University, Beijing, China.
  • Liu J; Nuclear Medicine Department, Beijing Friendship Hospital, Capital Medical University, Beijing, China.
  • Zhang SX; Nuclear Medicine Department, Beijing Friendship Hospital, Capital Medical University, Beijing, China.
  • Ren JL; Department of Pharmaceuticals Diagnostics, GE HealthCare, Beijing, China.
  • Wang W; Nuclear Medicine Department, Beijing Friendship Hospital, Capital Medical University, Beijing, China.
  • Yang J; Nuclear Medicine Department, Beijing Friendship Hospital, Capital Medical University, Beijing, China.
Quant Imaging Med Surg ; 14(4): 3131-3145, 2024 Apr 03.
Article en En | MEDLINE | ID: mdl-38617169
ABSTRACT

Background:

The MYCN copy number category is closely related to the prognosis of neuroblastoma (NB). Therefore, this study aimed to assess the predictive ability of 18F-fluorodeoxyglucose (18F-FDG) positron emission tomography/computed tomography (PET/CT) radiomic features for MYCN copy number in NB.

Methods:

A retrospective analysis was performed on 104 pediatric patients with NB that had been confirmed by pathology. To develop the Bio-omics model (B-model), which incorporated clinical and biological aspects, PET/CT radiographic features, PET quantitative parameters, and significant features with multivariable stepwise logistic regression were preserved. Important radiomics features were identified through least absolute shrinkage and selection operator (LASSO) and univariable analysis. On the basis of radiomics features obtained from PET and CT scans, the radiomics model (R-model) was developed. The significant bio-omics and radiomics features were combined to establish a Multi-omics model (M-model). The above 3 models were established to differentiate MYCN wild from MYCN gain and MYCN amplification (MNA). The calibration curve and receiver operating characteristic (ROC) curve analyses were performed to verify the prediction performance. Post hoc analysis was conducted to compare whether the constructed M-model can distinguish MYCN gain from MNA.

Results:

The M-model showed excellent predictive performance in differentiating MYCN wild from MYCN gain and MNA, which was better than that of the B-model and R-model [area under the curve (AUC) 0.83, 95% confidence interval (CI) 0.74-0.92 vs. 0.81, 95% CI 0.72-0.90 and 0.79, 95% CI 0.69-0.89]. The calibration curve showed that the M-model had the highest reliability. Post hoc analysis revealed the great potential of the M-model in differentiating MYCN gain from MNA (AUC 0.95, 95% CI 0.89-1).

Conclusions:

The M-model model based on bio-omics and radiomics features is an effective tool to distinguish MYCN copy number category in pediatric patients with NB.
Palabras clave

Texto completo: 1 Colección: 01-internacional Base de datos: MEDLINE Idioma: En Revista: Quant Imaging Med Surg Año: 2024 Tipo del documento: Article País de afiliación: China

Texto completo: 1 Colección: 01-internacional Base de datos: MEDLINE Idioma: En Revista: Quant Imaging Med Surg Año: 2024 Tipo del documento: Article País de afiliación: China
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