Development of a pre-operative scoring system for predicting risk of post-operative paediatric cerebellar mutism syndrome

Liu, Jo-Fen; Dineen, Robert A.; Avula, Shivaram; Chambers, Tom; Dutta, Manali; Jaspan, Tim; Macarthur, Donald; Howarth, Simon; Soria, Daniele; Quinlan, P; Harave, Srikrishna; Ong, Chan Chang; Mallucci, Conor; Kumar, Ram; Pizer, Barry; Walker, David

doi:10.1080/02688697.2018.1431204

Cited by 46 publications

(56 citation statements)

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“…The imaging features measured and scored in this study were carried out according to the methods used by Liu et al [19] and Zhang et al [20] (Table 1). For a definition of imaging features, we refer to the table from the publication by Liu et al [19] In addition, we decided to measure Zhang et al's D(sag) and d(sag) irrespective of the tumor compressing or invading the brainstem.…”

Section: Image Analysismentioning

confidence: 99%

“…Given the severity of these long-term impairments, prevention of pCMS is crucial. An accurate and easy to use risk model that predicts which patient is at high risk for developing pCMS, and which patient is not, would ameliorate preoperative information for patients and parents and could help to stratify patients for relatively sparing surgical techniques [19]. Liu et al developed a scoring system based on preoperative MRI to predict the chance of pCMS occurrence [19].…”

Section: Introductionmentioning

confidence: 99%

“…An accurate and easy to use risk model that predicts which patient is at high risk for developing pCMS, and which patient is not, would ameliorate preoperative information for patients and parents and could help to stratify patients for relatively sparing surgical techniques [19]. Liu et al developed a scoring system based on preoperative MRI to predict the chance of pCMS occurrence [19]. Through a retrospective cohort analysis, they identified five predictors that, when put into a model, yielded the highest accuracy and least number of false negatives: cerebellar hemisphere location of the tumor (preventive factor for pCMS), cerebellar hemisphere invasion, bilateral median cerebellar peduncle invasion and/or compression, dentate nucleus invasion, and age at imaging > 12.4 years.…”

Section: Introductionmentioning

confidence: 99%

“…In this retrospective case matched study of 46 medulloblastoma patients of which 23 had developed pCMS that they found as reproducible predictors: However, they did not as yet apply their risk factors into a predictive model. The primary focus of this paper was to apply the Liu et al scoring system to the children in our cohort and evaluate the reproducibility of their results to predict pCMS after cerebellar tumor surgery [19]. In this cohort, we also evaluated the validity of the measurements reported by Zhang et al [20] and aimed to ameliorate the prediction model, when applicable.…”

Section: Introductionmentioning

confidence: 99%

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Preoperative prediction of postoperative cerebellar mutism syndrome. Validation of existing MRI models and proposal of the new Rotterdam pCMS prediction model

2020

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Purpose Postoperative cerebellar mutism syndrome (pCMS) is a complication that may occur after pediatric fossa posterior tumor surgery. Liu et al. developed an MRI-based prediction model to estimate pCMS risk preoperatively. The goal of this study was to validate the model of Liu et al. and if validation was not as sensitive in our group as previously described to develop an easy to use, reliable, and sensitive preoperative risk prediction model for pCMS. Methods In this study, 121children with a fossa posterior tumor who underwent surgery at ErasmusMC/Sophia Children's Hospital, the Netherlands between 2004 and 2018 could be included. Twenty-six percent of them developed pCMS. Preoperative MRI were scored using the Liu et al. model. Results The Liu et al. model reached an accuracy of 78%, a sensitivity of 58%, and a specificity of 84% in our cohort. In a new risk model some of the variables of Liu et al. were included as well as some of the recently described preoperative MRI characteristics in pCMS patients by Zhang et al. The new model reached an accuracy of 87%, a sensitivity of 97%, and a specificity of 84% in our patient group. Conclusion Because the Liu et al. model did not provide an as accurate risk prediction in our cohort as was expected, we created a new risk prediction model that reached high model accuracy in our cohort that could assist neurosurgeons in determining their surgical tactics and help prepare high risk patients and their parents for this severe complication.

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Section: Image Analysismentioning

confidence: 99%

Section: Introductionmentioning

confidence: 99%

Section: Introductionmentioning

confidence: 99%

Section: Introductionmentioning

confidence: 99%

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Preoperative prediction of postoperative cerebellar mutism syndrome. Validation of existing MRI models and proposal of the new Rotterdam pCMS prediction model

2020

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“…It is of utmost importance to prepare parents and caregivers of children that have surgery for a posterior fossa tumor for the risk that their child will develop pCMS and inform them on the variety and severity of symptoms that may occur. Identification of existing risk factors/predictors for pCMS is essential and may include a pre-operative comprehensive baseline assessment of speech and language [18] and the use of a pre-operative MRI-based scoring scale [32].…”

Section: Conclusion and Thoughts On Further Researchmentioning

confidence: 99%

Post-operative cerebellar mutism syndrome: rehabilitation issues

et al. 2019

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Introduction Tumors of the cerebellum are the most common brain tumors in children. Modern treatment and aggressive surgery have improved the overall survival. Consequently, growing numbers of survivors are at high risk for developing adverse and long-term neurological deficits including deficits of cognition, behavior, speech, and language. Post-operative cerebellar mutism syndrome (pCMS) is a well-known and frequently occurring complication of cerebellar tumor surgery in children. In the acute stage, children with pCMS may show deterioration of cerebellar motor function as well as pyramidal and cranial neuropathies. Most debilitating is the mutism or the severe reduction of speech and a range of neurobehavioral symptoms that may occur. In the long term, children that recover from pCMS continue to have more motor, behavioral, and cognitive problems than children who did not develop pCMS after cerebellar tumor surgery. The severity of these long-term sequelae seems to be related to the length of the mute phase. Aim of this narrative review The impact of pCMS on patients and families cannot be overstated. This contribution aims to discuss the present knowledge on the natural course, recovery, and rehabilitation of children with pCMS. We suggest future priorities in developing rehabilitation programs in order to improve the long-term quality of life and participation of children after cerebellar tumor surgery and after pCMS in particular.

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Presurgical MRI‐Based Radiomics Models for Predicting Cerebellar Mutism Syndrome in Children With Posterior Fossa Tumors

Yang

et al. 2023

Magnetic Resonance Imaging

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BackgroundCurrent studies have indicated that tumoral morphologic features are associated with cerebellar mutism syndrome (CMS), but the radiomics application in CMS is scarce.PurposeTo develop a model for CMS discrimination based on multiparametric MRI radiomics in patients with posterior fossa tumors.Study TypeRetrospective.PopulationA total of 218 patients (males 132, females 86) with posterior fossa tumors, 169 of which were included in the MRI radiomics analysis. The MRI radiomics study cohort (169) was split into training (119) and testing (50) sets with a ratio of 7:3.Field/SequenceAll the MRI were acquired under 1.5/3.0 T scanners. T2‐weighted image (T2W), T1‐weighted (T1W), fluid attenuated inversion recovery (FLAIR), diffusion‐weighted imaging (DWI).AssessmentApparent diffusion coefficient (ADC) maps were generated from DWI. Each MRI dataset generated 1561 radiomics characteristics. Feature selection was performed with univariable logistic analysis, correlation analysis, and least absolute shrinkage and selection operator (LASSO) penalized logistic regression. Significant clinical features were selected with multivariable logistic analysis and used to constructed the clinical model. Radiomics models (based on T1W, T2W, FLAIR, DWI, ADC) were constructed with selected radiomics features. The mix model was based on the multiparametric MRI radiomics features.Statistical TestMultivariable logistic analysis was utilized during clinical features selection. Models' performance was evaluated using the area under the receiver operating characteristic (AUC) curve. Interobserver variability was assessed using Cohen's kappa. Significant threshold was set as P < 0.05.ResultsSex (aOR = 3.72), tumor location (aOR = 2.81), hydrocephalus (aOR = 2.14), and tumor texture (aOR = 5.08) were significant features in the multivariable analysis and were used to construct the clinical model (AUC = 0.79); totally, 33 radiomics features were selected to construct radiomics models (AUC = 0.63–0.93). Seven of the 33 radiomics features were selected for the mix model (AUC = 0.93).Data ConclusionMultiparametric MRI radiomics may be better at predicting CMS than single‐parameter MRI models and clinical model.Evidence Level4.Technical Efficacy2.

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Development of a pre-operative scoring system for predicting risk of post-operative paediatric cerebellar mutism syndrome

Cited by 46 publications

References 18 publications

Preoperative prediction of postoperative cerebellar mutism syndrome. Validation of existing MRI models and proposal of the new Rotterdam pCMS prediction model

Preoperative prediction of postoperative cerebellar mutism syndrome. Validation of existing MRI models and proposal of the new Rotterdam pCMS prediction model

Post-operative cerebellar mutism syndrome: rehabilitation issues

Presurgical MRI‐Based Radiomics Models for Predicting Cerebellar Mutism Syndrome in Children With Posterior Fossa Tumors

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