MRI surrogates for molecular subgroups of medulloblastoma

S. Perreault, V. Ramaswamy, A. S. Achrol, K. Chao, T. T. Liu, D. Shih, M. Remke, S. Schubert, E. Bouffet, P. G. Fisher, S. Partap, H. Vogel, M. D. Taylor, Yoon-Jae Cho, Kristen W. Yeom

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Abstract

BACKGROUND AND PURPOSE: Recently identified molecular subgroups of medulloblastoma have shown potential for improved risk stratification. We hypothesized that distinct MR imaging features can predict these subgroups. MATERIALS AND METHODS: All patients with a diagnosis of medulloblastoma at one institution, with both pretherapy MR imaging and surgical tissue, served as the discovery cohort (n = 47). MR imaging features were assessed by 3 blinded neuroradiologists. NanoString-based assay of tumor tissues was conducted to classify the tumors into the 4 established molecular subgroups (wingless, sonic hedgehog, group 3, and group 4). A second pediatric medulloblastoma cohort (n = 52) from an independent institution was used for validation of the MR imaging features predictive of the molecular subtypes. RESULTS: Logistic regression analysis within the discovery cohort revealed tumor location (P < .001) and enhancement pattern (P = .001) to be significant predictors of medulloblastoma subgroups. Stereospecific computational analyses confirmed that group 3 and 4 tumors predominated within the midline fourth ventricle (100%, P = .007), wingless tumors were localized to the cerebellar peduncle/cerebellopontine angle cistern with a positive predictive value of 100% (95% CI, 30%-100%), and sonic hedgehog tumors arose in the cerebellar hemispheres with a positive predictive value of 100% (95% CI, 59%-100%). Midline group 4 tumors presented with minimal/no enhancement with a positive predictive value of 91% (95% CI, 59%-98%). When we used the MR imaging feature-based regression model, 66% of medulloblastomas were correctly predicted in the discovery cohort, and 65%, in the validation cohort. CONCLUSIONS: Tumor location and enhancement pattern were predictive of molecular subgroups of pediatric medulloblastoma and may potentially serve as a surrogate for genomic testing.

Original languageEnglish (US)
Pages (from-to)1263-1269
Number of pages7
JournalAmerican Journal of Neuroradiology
Volume35
Issue number7
DOIs
StatePublished - Jan 1 2014
Externally publishedYes

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Medulloblastoma
Neoplasms
Pediatrics
Cerebellopontine Angle
Fourth Ventricle
Logistic Models
Regression Analysis

ASJC Scopus subject areas

  • Radiology Nuclear Medicine and imaging
  • Clinical Neurology

Cite this

Perreault, S., Ramaswamy, V., Achrol, A. S., Chao, K., Liu, T. T., Shih, D., ... Yeom, K. W. (2014). MRI surrogates for molecular subgroups of medulloblastoma. American Journal of Neuroradiology, 35(7), 1263-1269. https://doi.org/10.3174/ajnr.A3990

MRI surrogates for molecular subgroups of medulloblastoma. / Perreault, S.; Ramaswamy, V.; Achrol, A. S.; Chao, K.; Liu, T. T.; Shih, D.; Remke, M.; Schubert, S.; Bouffet, E.; Fisher, P. G.; Partap, S.; Vogel, H.; Taylor, M. D.; Cho, Yoon-Jae; Yeom, Kristen W.

In: American Journal of Neuroradiology, Vol. 35, No. 7, 01.01.2014, p. 1263-1269.

Research output: Contribution to journalArticle

Perreault, S, Ramaswamy, V, Achrol, AS, Chao, K, Liu, TT, Shih, D, Remke, M, Schubert, S, Bouffet, E, Fisher, PG, Partap, S, Vogel, H, Taylor, MD, Cho, Y-J & Yeom, KW 2014, 'MRI surrogates for molecular subgroups of medulloblastoma', American Journal of Neuroradiology, vol. 35, no. 7, pp. 1263-1269. https://doi.org/10.3174/ajnr.A3990
Perreault S, Ramaswamy V, Achrol AS, Chao K, Liu TT, Shih D et al. MRI surrogates for molecular subgroups of medulloblastoma. American Journal of Neuroradiology. 2014 Jan 1;35(7):1263-1269. https://doi.org/10.3174/ajnr.A3990
Perreault, S. ; Ramaswamy, V. ; Achrol, A. S. ; Chao, K. ; Liu, T. T. ; Shih, D. ; Remke, M. ; Schubert, S. ; Bouffet, E. ; Fisher, P. G. ; Partap, S. ; Vogel, H. ; Taylor, M. D. ; Cho, Yoon-Jae ; Yeom, Kristen W. / MRI surrogates for molecular subgroups of medulloblastoma. In: American Journal of Neuroradiology. 2014 ; Vol. 35, No. 7. pp. 1263-1269.
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abstract = "BACKGROUND AND PURPOSE: Recently identified molecular subgroups of medulloblastoma have shown potential for improved risk stratification. We hypothesized that distinct MR imaging features can predict these subgroups. MATERIALS AND METHODS: All patients with a diagnosis of medulloblastoma at one institution, with both pretherapy MR imaging and surgical tissue, served as the discovery cohort (n = 47). MR imaging features were assessed by 3 blinded neuroradiologists. NanoString-based assay of tumor tissues was conducted to classify the tumors into the 4 established molecular subgroups (wingless, sonic hedgehog, group 3, and group 4). A second pediatric medulloblastoma cohort (n = 52) from an independent institution was used for validation of the MR imaging features predictive of the molecular subtypes. RESULTS: Logistic regression analysis within the discovery cohort revealed tumor location (P < .001) and enhancement pattern (P = .001) to be significant predictors of medulloblastoma subgroups. Stereospecific computational analyses confirmed that group 3 and 4 tumors predominated within the midline fourth ventricle (100{\%}, P = .007), wingless tumors were localized to the cerebellar peduncle/cerebellopontine angle cistern with a positive predictive value of 100{\%} (95{\%} CI, 30{\%}-100{\%}), and sonic hedgehog tumors arose in the cerebellar hemispheres with a positive predictive value of 100{\%} (95{\%} CI, 59{\%}-100{\%}). Midline group 4 tumors presented with minimal/no enhancement with a positive predictive value of 91{\%} (95{\%} CI, 59{\%}-98{\%}). When we used the MR imaging feature-based regression model, 66{\%} of medulloblastomas were correctly predicted in the discovery cohort, and 65{\%}, in the validation cohort. CONCLUSIONS: Tumor location and enhancement pattern were predictive of molecular subgroups of pediatric medulloblastoma and may potentially serve as a surrogate for genomic testing.",
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T1 - MRI surrogates for molecular subgroups of medulloblastoma

AU - Perreault, S.

AU - Ramaswamy, V.

AU - Achrol, A. S.

AU - Chao, K.

AU - Liu, T. T.

AU - Shih, D.

AU - Remke, M.

AU - Schubert, S.

AU - Bouffet, E.

AU - Fisher, P. G.

AU - Partap, S.

AU - Vogel, H.

AU - Taylor, M. D.

AU - Cho, Yoon-Jae

AU - Yeom, Kristen W.

PY - 2014/1/1

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N2 - BACKGROUND AND PURPOSE: Recently identified molecular subgroups of medulloblastoma have shown potential for improved risk stratification. We hypothesized that distinct MR imaging features can predict these subgroups. MATERIALS AND METHODS: All patients with a diagnosis of medulloblastoma at one institution, with both pretherapy MR imaging and surgical tissue, served as the discovery cohort (n = 47). MR imaging features were assessed by 3 blinded neuroradiologists. NanoString-based assay of tumor tissues was conducted to classify the tumors into the 4 established molecular subgroups (wingless, sonic hedgehog, group 3, and group 4). A second pediatric medulloblastoma cohort (n = 52) from an independent institution was used for validation of the MR imaging features predictive of the molecular subtypes. RESULTS: Logistic regression analysis within the discovery cohort revealed tumor location (P < .001) and enhancement pattern (P = .001) to be significant predictors of medulloblastoma subgroups. Stereospecific computational analyses confirmed that group 3 and 4 tumors predominated within the midline fourth ventricle (100%, P = .007), wingless tumors were localized to the cerebellar peduncle/cerebellopontine angle cistern with a positive predictive value of 100% (95% CI, 30%-100%), and sonic hedgehog tumors arose in the cerebellar hemispheres with a positive predictive value of 100% (95% CI, 59%-100%). Midline group 4 tumors presented with minimal/no enhancement with a positive predictive value of 91% (95% CI, 59%-98%). When we used the MR imaging feature-based regression model, 66% of medulloblastomas were correctly predicted in the discovery cohort, and 65%, in the validation cohort. CONCLUSIONS: Tumor location and enhancement pattern were predictive of molecular subgroups of pediatric medulloblastoma and may potentially serve as a surrogate for genomic testing.

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