Evidence map›Paper›PMID 26692534›Full record

ArticleTranslational oncology2015

Diffusion-Weighted Imaging in Meningioma: Prediction of Tumor Grade and Association with Histopathological Parameters.

Alexey Surov, Sebastian Gottschling, Christian Mawrin, Julian Prell, Rolf Peter Spielmann, Andreas Wienke, Eckhard Fiedler

Abstract read
In one paragraph

Article in Translational oncology, 2015. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 61 papers, 1 of them a synthesis that pooled it.

0numbers the graph read from it
0cells of the map it votes in
61citing papers in PubMed, 1 pooled it
–field-weighted citation impact
1 · What the graph read from it

What it found

Each row is one number read from the abstract, on the scale the paper reported it, with its interval. Left of the dashed line favours the treatment, right favours the comparator. Under each row is the sentence it came from. New to these charts? A ten-minute tutorial.

The abstract states no effect estimate the extractor could read, or names no intervention and outcome on the map, so this paper lights no cell and moves no belief. It is still indexed, cited and linked below.

2 · The registry

The trial behind it

Trials whose registry record cites this paper, or whose number appears in the abstract. A trial that started after this paper was published is citing it as background, not reporting it.

Neither the registry nor the abstract names a trial number. If this is a trial report, that itself is worth knowing.

3 · Its place in the literature

Who cites it

61 citing papers in PubMed, 1 synthesis or guideline pooled it.

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1 more citing papers are in PubMed but not listed here.

4 · The record

Corrections and comments

PubMed lists nothing against this paper. Absence here is not a guarantee, only a check that was made.

5 · Who and what money

Authors and funding

7 authors.

Alexey SurovDepartment of Radiology, Martin-Luther-University Halle-Wittenberg, Ernst-Grube-Str. 40, 06097 Halle. Electronic address: alex.surow@medizin.uni-halle.de.
Sebastian GottschlingDepartment of Radiology, Martin-Luther-University Halle-Wittenberg, Ernst-Grube-Str. 40, 06097 Halle. Electronic address: sebastian.gottschling@googlemail.com.
Christian MawrinDepartment of Neuropathology, Otto-von-Guericke-University Magdeburg, Leipziger Str. 44, 39120 Magdeburg. Electronic address: christian.mawrin@med.ovgu.de.
Julian PrellDepartment of Neurosurgery, Martin-Luther-University Halle-Wittenberg, Ernst-Grube-Str. 40, 06097 Halle. Electronic address: julian.prell@medizin.uni-halle.de.
Rolf Peter SpielmannDepartment of Radiology, Martin-Luther-University Halle-Wittenberg, Ernst-Grube-Str. 40, 06097 Halle. Electronic address: rolf.spielmann@medizin.uni-halle.de.
Andreas WienkeInstitute of Medical Epidemiology, Biostatistics and Informatics, Martin-Luther-University Halle-Wittenberg, Magdeburger Straße 8, 06112 Halle. Electronic address: andreas.wienke@medizin.uni-halle.de.
Eckhard FiedlerDepartment of Dermatology (histopathological laboratory), Martin-Luther-University Halle-Wittenberg, Ernst-Grube-Str. 40, 06097 Halle. Electronic address: eckhard.fiedler@medizin.uni-halle.de.

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

objectivesTo analyze diffusion-weighted imaging (DWI) findings of meningiomas and to compare them with tumor grade, cell count, and proliferation index and to test a possibility of use of apparent diffusion coefficient (ADC) to differentiate benign from atypical/malignant tumors.

methodsForty-nine meningiomas were analyzed. DWI was done using a multislice single-shot echo-planar imaging sequence. A polygonal region of interest was drawn on ADC maps around the margin of the lesion. In all lesions, minimal ADC values (ADCmin) and mean ADC values (ADCmean) were estimated. Normalized ADC (NADC) was calculated in every case as a ratio ADCmean meningioma/ADCmean white matter. All meningiomas were surgically resected and analyzed histopathologically. The tumor proliferation index was estimated on Ki-67 antigen-stained specimens. Cell density was calculated. Collected data were evaluated by means of descriptive statistics. Analyses of ADC/NADC values were performed by means of two-sided t tests.

resultsThe mean ADCmean value was higher in grade I meningiomas in comparison to grade II/III tumors (0.96 vs 0.80 × 10(-3) mm(2)s(-1), P = .006). Grade II/III meningiomas showed lower NADC values in comparison to grade I tumors (1.05 vs 1.26, P = .015). There was no significant difference in ADCmin values between grade I and II/III tumors (0.69 vs 0.63 × 10(-3) mm(2)s(-1), P = .539). The estimated cell count varied from 486 to 2091 (mean value, 1158.20 ± 333.74; median value, 1108). There were no significant differences in cell count between grade I and grade II/III tumors (1163.93 vs 1123.86 cells, P = .77). The mean level of the proliferation index was 4.78 ± 5.08%, the range was 1% to 18%, and the median value was 2%. The proliferation index was statistically significant higher in grade II/III meningiomas in comparison to grade I tumors (15.43% vs 3.00%, P = .001). Ki-67 was negatively associated with ADCmean (r = -0.61, P < .001) and NADC (r = -0.60, P < .001). No significant correlations between cell count and ADCmean (r = -0.20, P = .164) or NADC (r = -0.25, P = .079) were found. ADCmin correlated statistically significant with cell count (r = -0.44, P = .002) but not with Ki-67 (r = -0.22, P = .129). Furthermore, the association between ADCmin and cell count was stronger in grade II/III tumors (r = -0.79, P = .036) versus grade I meningiomas (r = -0.41, P = .008). An ADCmean value of less than 0.85 × 10(-3) mm(2)s(-1) was determined as the threshold in differentiating between grade I and grade II/III meningiomas (sensitivity 72.9%, specificity 73.1%, accuracy 73.0%). The positive and negative predictive values were 33.3% and 96.8%, respectively. The same threshold ADCmean value was used in differentiating between tumors with Ki-67 level ≥5% and meningiomas with low proliferation index (Ki-67 <5%). This threshold yielded a sensitivity of 70.6%, a specificity of 81.2%, and an accuracy of 77.6%. The positive and negative predictive values were 66.6% and 83.9%, respectively.

conclusionsGrade II/III tumors had lower ADCmean values than grade I meningiomas. ADCmean correlated negatively with tumor proliferation index and ADCmin with tumor cell count. These associations were different in several meningiomas. ADCmean can be used for distinguishing between benign and atypical/malignant tumors.

Identifiers

PMID26692534
PMCPMC4700293

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