| Title |
Diffusion profiling of tumor volumes using a histogram approach can predict proliferation and further microarchitectural features in medulloblastoma
|
|---|---|
| Published in |
Child's Nervous System, May 2018
|
| DOI | 10.1007/s00381-018-3846-2 |
| Pubmed ID | |
| Authors |
Stefan Schob, Anne Beeskow, Julia Dieckow, Hans-Jonas Meyer, Matthias Krause, Clara Frydrychowicz, Franz-Wolfgang Hirsch, Alexey Surov |
| Abstract |
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. 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. 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). 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. |
X Demographics
The data shown below were collected from the profiles of 3 X users who shared this research output. Click here to find out more about how the information was compiled.
Geographical breakdown
| Country | Count | As % |
|---|---|---|
| United States | 1 | 33% |
| Unknown | 2 | 67% |
Demographic breakdown
| Type | Count | As % |
|---|---|---|
| Members of the public | 2 | 67% |
| Science communicators (journalists, bloggers, editors) | 1 | 33% |
Mendeley readers
The data shown below were compiled from readership statistics for 9 Mendeley readers of this research output. Click here to see the associated Mendeley record.
Geographical breakdown
| Country | Count | As % |
|---|---|---|
| Unknown | 9 | 100% |
Demographic breakdown
| Readers by professional status | Count | As % |
|---|---|---|
| Other | 2 | 22% |
| Student > Ph. D. Student | 2 | 22% |
| Lecturer | 1 | 11% |
| Student > Bachelor | 1 | 11% |
| Student > Master | 1 | 11% |
| Other | 0 | 0% |
| Unknown | 2 | 22% |
| Readers by discipline | Count | As % |
|---|---|---|
| Medicine and Dentistry | 4 | 44% |
| Physics and Astronomy | 2 | 22% |
| Biochemistry, Genetics and Molecular Biology | 1 | 11% |
| Unknown | 2 | 22% |
Attention Score in Context
This research output has an Altmetric Attention Score of 1. This is our high-level measure of the quality and quantity of online attention that it has received. This Attention Score, as well as the ranking and number of research outputs shown below, was calculated when the research output was last mentioned on 04 June 2018.
All research outputs
#17,974,941
of 23,083,773 outputs
Outputs from Child's Nervous System
#1,226
of 2,815 outputs
Outputs of similar age
#239,448
of 331,171 outputs
Outputs of similar age from Child's Nervous System
#41
of 89 outputs
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