18F-FDG PET/CT-based radiomics nomogram could predict bone marrow involvement in pediatric neuroblastoma

Feng, Ling; Yang, Xu; Lu, Xia; Kan, Ying; Wang, Chao; Sun, Dehui; Zhang, Hui; Wang, Wei; Yang, Jigang

doi:10.1186/s13244-022-01283-8

Cited by 13 publications

(6 citation statements)

References 34 publications

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“…In the radiomics model based on 18 F-FDG PET/CT images for identifying INPC subgroups established by Qian et al [ 18 ], the AUC in the training cohort and validation cohort was 0.877 and 0.868, respectively. This comparatively lower performance in comparison with other studies implies that INPC subtypes are not easily distinguishable [ 23 , 24 ].…”

Section: Discussioncontrasting

confidence: 60%

Radiomics analysis of contrast-enhanced computed tomography in predicting the International Neuroblastoma Pathology Classification in neuroblastoma

et al. 2023

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Purpose To predict the International Neuroblastoma Pathology Classification (INPC) in neuroblastoma using a computed tomography (CT)-based radiomics approach. Methods We enrolled 297 patients with neuroblastoma retrospectively and divided them into a training group (n = 208) and a testing group (n = 89). To balance the classes in the training group, a Synthetic Minority Over-sampling Technique was applied. A logistic regression radiomics model based on the radiomics features after dimensionality reduction was then constructed and validated in both the training and testing groups. To evaluate the diagnostic performance of the radiomics model, the receiver operating characteristic curve and calibration curve were utilized. Moreover, the decision curve analysis to assess the net benefits of the radiomics model at different high-risk thresholds was employed. Results Seventeen radiomics features were used to construct radiomics model. In the training group, radiomics model achieved an area under the curve (AUC), accuracy, sensitivity, and specificity of 0.851 (95% confidence interval (CI) 0.805–0.897), 0.770, 0.694, and 0.847, respectively. In the testing group, radiomics model achieved an AUC, accuracy, sensitivity, and specificity of 0.816 (95% CI 0.725–0.906), 0.787, 0.793, and 0.778, respectively. The calibration curve indicated that the radiomics model was well fitted in both the training and testing groups (p > 0.05). Decision curve analysis further confirmed that the radiomics model performed well at different high-risk thresholds. Conclusion Radiomics analysis of contrast-enhanced CT demonstrates favorable diagnostic capabilities in distinguishing the INPC subgroups of neuroblastoma. Graphical Abstract Critical relevance statement Radiomics features of contrast-enhanced CT images correlate with the International Neuroblastoma Pathology Classification (INPC) of neuroblastoma.

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Section: Discussioncontrasting

confidence: 60%

Radiomics analysis of contrast-enhanced computed tomography in predicting the International Neuroblastoma Pathology Classification in neuroblastoma

et al. 2023

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“…In one of the very rare studies investigating the role of PET/CT in detecting bone marrow involvement in NB, approximately 50 % of the patients were metastatic at the time of diagnosis and the most common site of metastasis was bone marrow in 26 patients [13]. In this study the sensitivity and specificity of PET/CT in detecting BMI were 100 % and 50 %, respectively.…”

Section: Overallmentioning

confidence: 52%

“…However, the replacement of PET/CT with BMB in a pediatric setting has not yet been established. Indeed, only a very limited number of pediatric studies comparing PET/CT and BMB have been conducted, not only in lymphomas but also in other childhood solid cancers [1,13,14,15,16].…”

Section: Introductionmentioning

confidence: 99%

The Role of FDG- PET/CT in Detecting Bone Marrow Involvement in Childhood Solid Tumors

Arslantaş,

Ayçiçek,

Esen Akkas

et al. 2024

Nuklearmedizin

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Purpose To compare the results of 18F-Fluorodeoxy positron emission tomography/computed tomography (18 F-FDG-PET/CT) and bone marrow biopsy (BMB) procedures in the initial evaluation of bone marrow involvement (BMI) in pediatric solid tumors. Methods We conducted a retrospective analysis of newly diagnosed pediatric cases with lymphoma, neuroblastoma, Ewing sarcoma, rhabdomyosarcoma. Each case underwent both PET-CT imaging and BMB. Presence of tumor infiltration in BMB specimens and/or positive FDG-PET/CT findings indicate as BMI were regarded as true positive results. Results Sixty-four patients were included in the study. BMI was detected in 23/64 (36%) patients, FDG-PET/CT imaging and BMB results were concordant in 54/64 patients. In 9/64 patients the finding was FDG-PET/CT (+), BMB (-) indicating a false negative BMB result. In only 1/64 patients FDG- PET/CT (-), BMB (+), indicating a false negative FDG-PET/CT result. In the whole patient group, the sensitivity, specificity, positive predictive value and negative predictive value of PET/CT and BMB in detecting bone marrow involvement were 95.6%, 100%, 100% and 97.6% and 60.8 %, 100%, 100% and 82%, respectively. Conclusion PET/CT has a high sensitivity and specificity for the assessing marrow involvement in pediatric solid tumors. We believe that PET/CT imaging should be performed as the first step in diagnostic staging, and BMB may not be necessary in every patient, only in patients with suspicious PET/CT results for bone marrow involvement. Additionally, for a more precise determination of bone marrow involvement, it is reasonable to perform BMB from FDG-retaining areas, using PET/CT as a guide tool.

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“…Our results proved valuable in stratifying and distinguishing high-risk groups with AUCs of 0.903 and 0.876, respectively, and seemed suitable for clinical application. In recent years, several radiomics studies of malignant PNTs have reported features associated with the prediction of tumor histology, [23] MYCN amplification status, [24][25][26] bone marrow involvement, [27] response to neoadjuvant chemotherapy, [28] recurrence, [29] prognosis, [30] and differentiation between highrisk and non-high-risk groups. [31] Nearly half of the radiomics studies were based on 18 F-fluorodeoxyglucose positron emission tomography/computed tomography ( 18 F-FDG PET/CT).…”

Section: Discussionmentioning

confidence: 99%

Computed tomography-based radiomics to assess risk stratification in pediatric malignant peripheral neuroblastic tumors

Wang,

et al. 2023

Medicine

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This study aimed to develop and validate an analysis system based on preoperative computed tomography (CT) to predict the risk stratification in pediatric malignant peripheral neuroblastic tumors (PNTs). A total of 405 patients with malignant PNTs (184 girls and 221 boys; mean age, 33.8 ± 29.1 months) were retrospectively evaluated between January 2010 and June 2018. Radiomic features were extracted from manually segmented tumors on preoperative CT images. Spearman’s rank correlation coefficient and the least absolute shrinkage and selection operator (LASSO) were used to eliminate redundancy and select features. A risk model was built to stratify low-, intermediate-, and high-risk groups. An image-defined risk factor (IDRFs) model was developed to classify 266 patients with malignant PNTs and one or more IDRFs into high-risk and non-high-risk groups. The performance of the predictive models was evaluated with respect to accuracy (Acc) and receiver operating characteristic (ROC) curve, including the area under the ROC curve (AUC). The risk model demonstrated good discrimination capability, with an area under the curve (AUC) of 0.903 to distinguish high-risk from non-high-risk groups, and 0.747 to classify intermediate- and low-risk groups. In the IDRF-based risk model with the number of IDRFs, the AUC was 0.876 for classifying the high-risk and non-high-risk groups. Radiomic analysis based on preoperative CT images has the potential to stratify the risk of pediatric malignant PNTs. It had outstanding efficiency in distinguishing patients in the high-risk group, and this predictive model of risk stratification could assist in selecting optimal aggressive treatment options.

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18F-FDG PET/CT-based radiomics nomogram could predict bone marrow involvement in pediatric neuroblastoma

Cited by 13 publications

References 34 publications

Radiomics analysis of contrast-enhanced computed tomography in predicting the International Neuroblastoma Pathology Classification in neuroblastoma

Radiomics analysis of contrast-enhanced computed tomography in predicting the International Neuroblastoma Pathology Classification in neuroblastoma

The Role of FDG- PET/CT in Detecting Bone Marrow Involvement in Childhood Solid Tumors

Computed tomography-based radiomics to assess risk stratification in pediatric malignant peripheral neuroblastic tumors

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