Magnetic resonance imaging to diagnose leptomeningeal spread of medulloblastoma in children: Decreasing diagnostic uncertainty, moving in new directions

Soares, Bruno P.; Poretti, Andrea; Huisman, Thierry A.G.M.

doi:10.1002/pbc.26514

Cited by 3 publications

(5 citation statements)

References 11 publications

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“…Children without CSF dissemination were identi ed by negative head and spine MRI and outcome at the one-year follow up. This diagnosis strategy is consistent with the literature determining the status of CSF dissemination by using overall survival [6] . The equivocal ndings in spine MRI such as linear enhancement, clumping and enhancement of nerve roots can be misdiagnosed as CSF dissemination, all of which can be identi ed in preoperative MRI.…”

Section: Discussionsupporting

confidence: 89%

“…Both MRI of the CNS and CSF cytology will appear false positive and negative. On one hand, MRI of the CNS is not able to detect early dissemination, while on the other hand, the equivocal ndings such as enhanced meningeal thickening and nerve roots clumping may be misdiagnosed as dissemination [5,6]. Because of technical or sampling problems, CSF cytology may fail to detect the tumor cells.…”

Section: Introductionmentioning

confidence: 99%

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Clinical-MRI Radiomics Enables the Prediction of Preoperative Cerebral Spinal Fluid Dissemination in Children With Medulloblastoma 

Zheng

et al. 2020

Preprint

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Background: Medulloblastoma (MB) is the most common pediatric embryonal tumor. Accurate identification of cerebral spinal fluid (CSF) dissemination is important in prognosis prediction. Both MRI of the central nervous system (CNS) and CSF cytology will appear false positive and negative. Our objective was to investigate the added value of enhanced T1 weighted images-based radiomics features to clinical characteristics in predicting preoperative CSF dissemination for children with MB.Materials and Methods: This retrospective study included 84 children with histopathologically confirmed MB (60 children in the training cohort and 24 children in the validation cohort). The children with normal head and spine magnetic resonance images (MRI) and no subsequent dissemination in one year were diagnosed as non-CSF dissemination. The CSF dissemination was manifested as intra-cranial or -spinal nodular enhanced lesions. Clinical features and conventional MRI features were collected and evaluated. A total of 385 radiomics features were extracted from enhanced T1 weighted images. Minimum redundancy, maximum correlation and least absolute shrinkage and selection operator were performed to select the features with the best performance in predicting preoperative CSF dissemination. A combined clinical-MRI radiomics prediction model was developed using multivariable logistic regression. Receiver operating curve analysis was used to validate the predictive performance. Nomogram and decision curve analysis (DCA) were developed to evaluate the clinical utility of combined model.Results: Thirty-one children were confirmed to have preoperative CSF dissemination. One clinical and nine radiomics features were selected for predicting preoperative CSF dissemination. The combined model incorporating clinical and radiomics features had best predictive performance both in the training and validation cohorts. In the validation cohort, a threshold of 0.311 yielded an area under the curve of 0.87, a sensitivity of 77.8%, a specificity of 86.7%, and an accuracy of 83.3%. The clinical utility of the model was confirmed by a clinical-MRI radiomics nomogram and DCA. Conclusions: The combined model incorporating clinical, conventional MRI and radiomics features could be applied to predict preoperative CSF dissemination for children with MB as a noninvasive biomarker, which could aid in risk evaluation.

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Section: Discussionsupporting

confidence: 89%

Section: Introductionmentioning

confidence: 99%

Clinical-MRI Radiomics Enables the Prediction of Preoperative Cerebral Spinal Fluid Dissemination in Children With Medulloblastoma 

Zheng

et al. 2020

Preprint

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“…Children without CSF dissemination were identified by negative head and spine MRI and outcome at the 1-year follow-up. This diagnosis strategy is consistent with the literature determining the status of CSF dissemination by using overall survival [ 6 ]. The equivocal findings in spine MRI such as linear enhancement, clumping, and enhancement of nerve roots can be misdiagnosed as CSF dissemination, all of which can be identified in preoperative MRI.…”

Section: Discussionsupporting

confidence: 88%

“…Both MRI of the CNS and CSF cytology will appear false positive and negative. On the one hand, MRI of the CNS is not able to detect early dissemination, while on the other hand, the equivocal findings such as enhanced meningeal thickening and nerve roots clumping may be misdiagnosed as dissemination [ 5 , 6 ]. Because of technical or sampling problems, CSF cytology may fail to detect the tumor cells.…”

Section: Introductionmentioning

confidence: 99%

Clinical-MRI radiomics enables the prediction of preoperative cerebral spinal fluid dissemination in children with medulloblastoma

Zheng

Liu

et al. 2021

World J Surg Onc

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Background Medulloblastoma (MB) is the most common pediatric embryonal tumor. Accurate identification of cerebral spinal fluid (CSF) dissemination is important in prognosis prediction. Both MRI of the central nervous system (CNS) and CSF cytology will appear false positive and negative. Our objective was to investigate the added value of preoperative-enhanced T1-weighted image-based radiomic features to clinical characteristics in predicting preoperative CSF dissemination for children with MB. Materials and methods This retrospective study included 84 children with histopathologically confirmed MB between November 2006 and November 2018 (training cohort, n=60; internal validation cohort, n=24). A set of cases between December 2018 and February 2020 were used for external validation (n=40). The children with normal head and spine magnetic resonance images (MRI) and no subsequent dissemination in 1 year were diagnosed as non-CSF dissemination. The CSF dissemination was manifested as intracranial or intraspinal nodular-enhanced lesions. Clinical features were collected, and conventional MRI features of preoperative head MRI examinations were evaluated. A total of 385 radiomic features were extracted from preoperative-enhanced T1-weighted images. Minimum redundancy, maximum correlation, and least absolute shrinkage and selection operator were performed to select the features with the best performance in predicting preoperative CSF dissemination. A combined clinical-MRI radiomic prediction model was developed using multivariable logistic regression. Receiver operating curve analysis (ROC) was used to validate the predictive performance. Nomogram and decision curve analysis (DCA) were developed to evaluate the clinical utility of the combined model. Results One clinical and nine radiomic features were selected for predicting preoperative CSF dissemination. The combined model incorporating clinical and radiomic features had the best predictive performance in the training cohort with an AUC of 0.89. This was validated in the internal and external cohorts with AUCs of 0.87 and 0.73. The clinical utility of the model was confirmed by a clinical-MRI radiomic nomogram and DCA. Conclusions The combined model incorporating clinical, conventional MRI, and radiomic features could be applied to predict preoperative CSF dissemination for children with MB as a noninvasive biomarker, which could aid in risk evaluation.

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“…These features are commonly encountered in SHH medulloblastomas and represent the sequelae of posttreatment inflammatory changes rather than recurrence or metastasis. Awareness of these equivocal findings on serial images is essential to obviate the need for more aggressive therapy (139,140).…”

Section: Role Of Imagingmentioning

confidence: 99%

Pediatric Brain Tumor Genetics: What Radiologists Need to Know

et al. 2018

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Brain tumors are the most common solid tumors in the pediatric population. Pediatric neuro-oncology has changed tremendously during the past decade owing to ongoing genomic advances. The diagnosis, prognosis, and treatment of pediatric brain tumors are now highly reliant on the genetic profile and histopathologic features of the tumor rather than the histopathologic features alone, which previously were the reference standard. The clinical information expected to be gleaned from radiologic interpretations also has evolved. Imaging is now expected to not only lead to a relevant short differential diagnosis but in certain instances also aid in predicting the specific tumor and subtype and possibly the prognosis. These processes fall under the umbrella of radiogenomics. Therefore, to continue to actively participate in patient care and/or radiogenomic research, it is important that radiologists have a basic understanding of the molecular mechanisms of common pediatric central nervous system tumors. The genetic features of pediatric low-grade gliomas, high-grade gliomas, medulloblastomas, and ependymomas are reviewed; differences between pediatric and adult gliomas are highlighted; and the critical oncogenic pathways of each tumor group are described. The role of the mitogen-activated protein kinase pathway in pediatric low-grade gliomas and of histone mutations as epigenetic regulators in pediatric high-grade gliomas is emphasized. In addition, the oncogenic drivers responsible for medulloblastoma, the classification of ependymomas, and the associated imaging correlations and clinical implications are discussed. © RSNA, 2018 • Abbreviations: CDK = cyclin-dependent kinase, CNS = central nervous system, DIPG = diffuse intrinsic pontine glioma, FGFR1 = fibroblast growth factor receptor 1, GBM = glioblastoma multiforme, HGG = high-grade glioma, IDH = isocitrate dehydrogenase, IDH1 = IDH 1, LGG = low-grade glioma, MAPK = mitogenactivated protein kinase, MEK = MAPK/extracellular signal-regulated kinase (ERK) kinase, PXA = pleomorphic xanthoastrocytoma, SHH = sonic hedgehog, SUFU = suppressor of fused, WHO = World Health Organization, Wnt = wingless RadioGraphics 2018; 38:2102-2122

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Magnetic resonance imaging to diagnose leptomeningeal spread of medulloblastoma in children: Decreasing diagnostic uncertainty, moving in new directions

Cited by 3 publications

References 11 publications

Clinical-MRI Radiomics Enables the Prediction of Preoperative Cerebral Spinal Fluid Dissemination in Children With Medulloblastoma

Clinical-MRI Radiomics Enables the Prediction of Preoperative Cerebral Spinal Fluid Dissemination in Children With Medulloblastoma

Clinical-MRI radiomics enables the prediction of preoperative cerebral spinal fluid dissemination in children with medulloblastoma

Pediatric Brain Tumor Genetics: What Radiologists Need to Know

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Magnetic resonance imaging to diagnose leptomeningeal spread of medulloblastoma in children: Decreasing diagnostic uncertainty, moving in new directions

Cited by 3 publications

References 11 publications

Clinical-MRI&nbsp;Radiomics Enables the Prediction of Preoperative Cerebral Spinal Fluid Dissemination in Children With Medulloblastoma&nbsp;

Clinical-MRI&nbsp;Radiomics Enables the Prediction of Preoperative Cerebral Spinal Fluid Dissemination in Children With Medulloblastoma&nbsp;

Clinical-MRI radiomics enables the prediction of preoperative cerebral spinal fluid dissemination in children with medulloblastoma

Pediatric Brain Tumor Genetics: What Radiologists Need to Know

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Clinical-MRI Radiomics Enables the Prediction of Preoperative Cerebral Spinal Fluid Dissemination in Children With Medulloblastoma

Clinical-MRI Radiomics Enables the Prediction of Preoperative Cerebral Spinal Fluid Dissemination in Children With Medulloblastoma