P18.10.B Natural history of meningiomas - a serial volumetric analysis of 240 tumors. (5th September 2022)
- Record Type:
- Journal Article
- Title:
- P18.10.B Natural history of meningiomas - a serial volumetric analysis of 240 tumors. (5th September 2022)
- Main Title:
- P18.10.B Natural history of meningiomas - a serial volumetric analysis of 240 tumors
- Authors:
- Thomann, P
Häni, L
Vulcu, S
Schütz, A
Frosch, M
Jesse, C M
El-Koussy, M
Söll, N
Hakim, A
Raabe, A
Schucht, P - Abstract:
- Abstract: Background: The management of asymptomatic intracranial meningiomas is controversial. Through the assessment of growth predictors, we aimed to create the basis for practicable clinical pathways for the management of these tumors. Material and Methods: We volumetrically analyzed meningiomas radiologically diagnosed at our institution between 2003 and 2015. For this purpose, we used exclusively thin-layered MR images (i.e. ≤ 2mm slice thickness). The primary endpoint was tumor growth defined as a 14.35% increase in tumor volume. We identified predictive clinical and radiological characteristics and used the significant variables from a multivariable regression model to construct a decision tree based on the exhaustive Chi-squared Automatic Interaction Detection (exhaustive CHAID) algorithm. Results: Of 240 meningiomas, 159 (66.3%) demonstrated growth during a mean observation period of 46.9 months. On multivariable logistic regression analysis, older age (OR=0.979 (0.958-1.000), p=0.048) and presence of calcification (OR=0.442 (0.224-0.872), p=0.019) had a negative predictive value for tumor growth, while T2-signal iso-/hyperintensity (OR=4.415 (2.056-9.479), p<0.001) had a positive predictive value. A decision tree model yielded three growth risk groups based on T2-signal intensity and presence of calcifications with a proportion of growing tumors of 34.1% in the low risk group, 60.0% in the intermediate risk group and 80.2% in the high risk group. Median tumorAbstract: Background: The management of asymptomatic intracranial meningiomas is controversial. Through the assessment of growth predictors, we aimed to create the basis for practicable clinical pathways for the management of these tumors. Material and Methods: We volumetrically analyzed meningiomas radiologically diagnosed at our institution between 2003 and 2015. For this purpose, we used exclusively thin-layered MR images (i.e. ≤ 2mm slice thickness). The primary endpoint was tumor growth defined as a 14.35% increase in tumor volume. We identified predictive clinical and radiological characteristics and used the significant variables from a multivariable regression model to construct a decision tree based on the exhaustive Chi-squared Automatic Interaction Detection (exhaustive CHAID) algorithm. Results: Of 240 meningiomas, 159 (66.3%) demonstrated growth during a mean observation period of 46.9 months. On multivariable logistic regression analysis, older age (OR=0.979 (0.958-1.000), p=0.048) and presence of calcification (OR=0.442 (0.224-0.872), p=0.019) had a negative predictive value for tumor growth, while T2-signal iso-/hyperintensity (OR=4.415 (2.056-9.479), p<0.001) had a positive predictive value. A decision tree model yielded three growth risk groups based on T2-signal intensity and presence of calcifications with a proportion of growing tumors of 34.1% in the low risk group, 60.0% in the intermediate risk group and 80.2% in the high risk group. Median tumor volume doubling time (Td) was 185.7 months in the low risk, 100.1 months in the intermediate risk and 51.7 months in the high risk group (p<0.001). While 0% of meningiomas in the low and intermediate risk group had a Td of ≤12 months, 8.9% in the high risk group did so (p=0.021). Conclusion: Most meningiomas demonstrated growth during follow-up. The presence or absence of calcifications and the signal intensity on T2-weighted imaging allow a practical and simple stratification of meningiomas into low, intermediate and high risk tumors. Small tumors in the low or intermediate risk categories can be monitored with longer follow-up intervals, whereas in the high risk category proactive management decisions can be justified. … (more)
- Is Part Of:
- Neuro-oncology. Volume 24(2022)Supplement 2
- Journal:
- Neuro-oncology
- Issue:
- Volume 24(2022)Supplement 2
- Issue Display:
- Volume 24, Issue 2 (2022)
- Year:
- 2022
- Volume:
- 24
- Issue:
- 2
- Issue Sort Value:
- 2022-0024-0002-0000
- Page Start:
- ii96
- Page End:
- ii96
- Publication Date:
- 2022-09-05
- Subjects:
- Brain Neoplasms -- Periodicals
Brain -- Tumors -- Periodicals
Brain -- Cancer -- Periodicals
Nervous system -- Cancer -- Periodicals
616.99481 - Journal URLs:
- http://neuro-oncology.dukejournals.org/ ↗
http://neuro-oncology.oxfordjournals.org/ ↗
http://www.oxfordjournals.org/content?genre=journal&issn=1522-8517 ↗
http://ukcatalogue.oup.com/ ↗ - DOI:
- 10.1093/neuonc/noac174.337 ↗
- Languages:
- English
- ISSNs:
- 1522-8517
- Deposit Type:
- Legaldeposit
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- Available online (eLD content is only available in our Reading Rooms) ↗
- Physical Locations:
- British Library DSC - 6081.288000
British Library DSC - BLDSS-3PM
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