Literature DB >> 29855678

Diffusion profiling of tumor volumes using a histogram approach can predict proliferation and further microarchitectural features in medulloblastoma.

Stefan Schob1, Anne Beeskow2, Julia Dieckow3, Hans-Jonas Meyer4, Matthias Krause5, Clara Frydrychowicz6, Franz-Wolfgang Hirsch2, Alexey Surov4.   

Abstract

BACKGROUND: Medulloblastomas are the most common central nervous system tumors in childhood. Treatment and prognosis strongly depend on histology and transcriptomic profiling. However, the proliferative potential also has prognostical value. Our study aimed to investigate correlations between histogram profiling of diffusion-weighted images and further microarchitectural features.
MATERIAL AND METHODS: Seven patients (age median 14.6 years, minimum 2 years, maximum 20 years; 5 male, 2 female) were included in this retrospective study. Using a Matlab-based analysis tool, histogram analysis of whole apparent diffusion coefficient (ADC) volumes was performed.
RESULTS: ADC entropy revealed a strong inverse correlation with the expression of the proliferation marker Ki67 (r = - 0.962, p = 0.009) and with total nuclear area (r = - 0.888, p = 0.044). Furthermore, ADC percentiles, most of all ADCp90, showed significant correlations with Ki67 expression (r = 0.902, p = 0.036). DISCUSSION AND
CONCLUSION: Diffusion histogram profiling of medulloblastomas provides valuable in vivo information which potentially can be used for risk stratification and prognostication. First of all, entropy revealed to be the most promising imaging biomarker. However, further studies are warranted.

Entities:  

Keywords:  ADC histogram analysis; Diffusion-weighted imaging; Histopathologic features; Ki-67; Medulloblastoma

Mesh:

Year:  2018        PMID: 29855678     DOI: 10.1007/s00381-018-3846-2

Source DB:  PubMed          Journal:  Childs Nerv Syst        ISSN: 0256-7040            Impact factor:   1.475


  22 in total

1.  MR Imaging Characteristics of Wingless-Type-Subgroup Pediatric Medulloblastoma.

Authors:  Z Patay; L A DeSain; S N Hwang; A Coan; Y Li; D W Ellison
Journal:  AJNR Am J Neuroradiol       Date:  2015-09-03       Impact factor: 3.825

2.  ADC Histogram Analysis of Cervical Cancer Aids Detecting Lymphatic Metastases-a Preliminary Study.

Authors:  Stefan Schob; Hans Jonas Meyer; Nikolaos Pazaitis; Dominik Schramm; Kristina Bremicker; Marc Exner; Anne Kathrin Höhn; Nikita Garnov; Alexey Surov
Journal:  Mol Imaging Biol       Date:  2017-12       Impact factor: 3.488

3.  Histological variants of medulloblastoma are the most powerful clinical prognostic indicators.

Authors:  Maura Massimino; Manila Antonelli; Lorenza Gandola; Rosalba Miceli; Bianca Pollo; Veronica Biassoni; Elisabetta Schiavello; Francesca Romana Buttarelli; Filippo Spreafico; Paola Collini; Felice Giangaspero
Journal:  Pediatr Blood Cancer       Date:  2012-06-12       Impact factor: 3.167

4.  Common pediatric cerebellar tumors: correlation between cell densities and apparent diffusion coefficient metrics.

Authors:  Korgün Koral; Derek Mathis; Barjor Gimi; Lynn Gargan; Bradley Weprin; Daniel C Bowers; Linda Margraf
Journal:  Radiology       Date:  2013-04-05       Impact factor: 11.105

5.  Use of Diffusion Weighted Imaging in Differentiating Between Maligant and Benign Meningiomas. A Multicenter Analysis.

Authors:  Alexey Surov; Daniel T Ginat; Eser Sanverdi; C C Tchoyoson Lim; Bahattin Hakyemez; Akira Yogi; Teresa Cabada; Andreas Wienke
Journal:  World Neurosurg       Date:  2015-10-31       Impact factor: 2.104

Review 6.  Childhood medulloblastoma.

Authors:  Maura Massimino; Veronica Biassoni; Lorenza Gandola; Maria Luisa Garrè; Gemma Gatta; Felice Giangaspero; Geraldina Poggi; Stefan Rutkowski
Journal:  Crit Rev Oncol Hematol       Date:  2016-06-15       Impact factor: 6.312

7.  Molecular subgroups of medulloblastoma: the current consensus.

Authors:  Michael D Taylor; Paul A Northcott; Andrey Korshunov; Marc Remke; Yoon-Jae Cho; Steven C Clifford; Charles G Eberhart; D Williams Parsons; Stefan Rutkowski; Amar Gajjar; David W Ellison; Peter Lichter; Richard J Gilbertson; Scott L Pomeroy; Marcel Kool; Stefan M Pfister
Journal:  Acta Neuropathol       Date:  2011-12-02       Impact factor: 17.088

Review 8.  Improving tumour heterogeneity MRI assessment with histograms.

Authors:  N Just
Journal:  Br J Cancer       Date:  2014-09-30       Impact factor: 7.640

9.  Correlation between apparent diffusion coefficient (ADC) and cellularity is different in several tumors: a meta-analysis.

Authors:  Alexey Surov; Hans Jonas Meyer; Andreas Wienke
Journal:  Oncotarget       Date:  2017-05-10

10.  Signal Intensities in Preoperative MRI Do Not Reflect Proliferative Activity in Meningioma.

Authors:  Stefan Schob; Clara Frydrychowicz; Matthias Gawlitza; Lionel Bure; Matthias Preuß; Karl-Titus Hoffmann; Alexey Surov
Journal:  Transl Oncol       Date:  2016-07-08       Impact factor: 4.243

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  3 in total

1.  Rheologically Essential Surfactant Proteins of the CSF Interacting with Periventricular White Matter Changes in Hydrocephalus Patients - Implications for CSF Dynamics and the Glymphatic System.

Authors:  Alexander Weiß; Matthias Krause; Anika Stockert; Cindy Richter; Joana Puchta; Pervinder Bhogal; Karl-Titus Hoffmann; Alexander Emmer; Ulf Quäschling; Cordula Scherlach; Wolfgang Härtig; Stefan Schob
Journal:  Mol Neurobiol       Date:  2019-05-24       Impact factor: 5.590

2.  The role of apparent diffusion coefficient histogram metrics for differentiating pediatric medulloblastoma histological variants and molecular groups.

Authors:  Fabrício Guimarães Gonçalves; Luis Octavio Tierradentro-Garcia; Jorge Du Ub Kim; Alireza Zandifar; Adarsh Ghosh; Angela N Viaene; Dmitry Khrichenko; Savvas Andronikou; Arastoo Vossough
Journal:  Pediatr Radiol       Date:  2022-07-08

Review 3.  Advancements in Neuroimaging to Unravel Biological and Molecular Features of Brain Tumors.

Authors:  Francesco Sanvito; Antonella Castellano; Andrea Falini
Journal:  Cancers (Basel)       Date:  2021-01-23       Impact factor: 6.639

  3 in total

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