Skip to main content

Advertisement

Log in

Comparison of ABC/2 estimation and a volumetric computerized method for measurement of meningiomas using magnetic resonance imaging

  • Clinical Study
  • Published:
Journal of Neuro-Oncology Aims and scope Submit manuscript

Abstract

Introduction

Measurement of tumor growth rates over time for patients with meningiomas has important prognostic and therapeutic implications. Our objective was to compare two methods of measuring meningioma volume: (1) the simplified ellipsoid (ABC/2) method; and (2) perimetric volume measurements using imaging software modules.

Methods

Patients with conservatively managed meningiomas for at least 1.5 years were retrospectively identified from the VCU Brain and Spine Tumor Registry over a 10-year period (2005–2015). Tumor volumes were independently measured using the simplified ellipsoid and computerized perimetric methods. Intra class correlations (CC) and Bland–Altman analyses were performed.

Results

A total of 26 patients representing 29 tumors were identified. Across 146 images, there were 24 (16%) images that were non-measurable using standard application commands with the computerized perimetric method. The mean volume obtained using the ABC/2 and computerized perimetric methods were 3.2 ± 3.4 cm3 and 3.4 ± 3.5 cm3, respectively. The mean volume difference was 0.2 cm3 (SE = 0.12; p = 0.10) across measurement methods. The concordance correlation coefficient (CCC) between methods was 0.95 (95% CI 0.91, 0.98).

Conclusions

There is excellent correlation between the simplified ellipsoid and computerized perimetric methods of volumetric analysis for conservatively managed meningiomas. The simplified ellipsoid method remains an excellent method for meningioma volume assessment and had an advantage over the perimetric method which failed to allow measurement of roughly one in six tumors on imaging.

This is a preview of subscription content, log in via an institution to check access.

Access this article

Price excludes VAT (USA)
Tax calculation will be finalised during checkout.

Instant access to the full article PDF.

Fig. 1
Fig. 2
Fig. 3
Fig. 4

Similar content being viewed by others

Data availability

The datasets generated during and/or analyzed during the current study are available from the corresponding author on reasonable request.

References

  1. Dolecek TA, Propp JM, Stroup NE, Kruchko C (2012) CBTRUS statistical report: primary brain and central nervous system tumors diagnosed in the united states in 2005–2009. Neuro Oncol 14(Suppl 5):v1–v49. https://doi.org/10.1093/neuonc/nos218

    Article  PubMed  PubMed Central  Google Scholar 

  2. Krampla W, Newrkla S, Pfisterer W et al (2004) Frequency and risk factors for meningioma in clinically healthy 75-year-old patients: results of the transdanube ageing study (VITA). Cancer 100(6):1208–1212. https://doi.org/10.1002/cncr.20088

    Article  PubMed  Google Scholar 

  3. Vernooij MW, Ikram MA, Tanghe HL et al (2007) Incidental findings on brain MRI in the general population. N Engl J Med 357(18):1821–1828

    Article  CAS  Google Scholar 

  4. Wiemels J, Wrensch M, Claus EB (2010) Epidemiology and etiology of meningioma. J Neurooncol 99(3):307–314. https://doi.org/10.1007/s11060-010-0386-3

    Article  PubMed  PubMed Central  Google Scholar 

  5. Chamoun R, Krisht KM, Couldwell WT (2011) Incidental meningiomas. Neurosurg Focus 31(6):E19. https://doi.org/10.3171/2011.9.FOCUS11220

    Article  PubMed  Google Scholar 

  6. Brem SS, Bierman PJ, Black P et al (2005) Central nervous system cancers: clinical practice guidelines in oncology. J Natl Compr Canc Netw 3:644–690

    Article  Google Scholar 

  7. Hashiba T, Hashimoto N, Izumoto S et al (2009) Serial volumetric assessment of the natural history and growth pattern of incidentally discovered meningiomas. J Neurosurg 110(4):675–684. https://doi.org/10.3171/2008.8.JNS08481

    Article  PubMed  Google Scholar 

  8. Nakamura M, Roser F, Michel J, Jacobs C, Samii M (2003) The natural history of incidental meningiomas. Neurosurgery 53(1):62–70. (discussion 70-1)

    Article  Google Scholar 

  9. Chang V, Narang J, Schultz L et al (2012) Computer-aided volumetric analysis as a sensitive tool for the management of incidental meningiomas. Acta Neurochir (Wien) 154(4):589–597. https://doi.org/10.1007/s00701-012-1273-9. (discussion 597)

    Article  Google Scholar 

  10. Zeidman LA, Ankenbrandt WJ, Du H, Paleologos N, Vick NA (2008) Growth rate of non-operated meningiomas. J Neurol 255(6):891–895. https://doi.org/10.1007/s00415-008-0801-2

    Article  CAS  PubMed  Google Scholar 

  11. Xue W, Vegunta S, Zwart CM, Aguilar MI, Patel AC, Hoxworth JM et al (2017) Retrospective validation of a computer-assisted quantification model of intracerebral hemorrhage volume on accuracy, precision, and acquisition time, compared with standard ABC/2 manual volume calculation. Am J Neuroradiol 38(8):1536–1542. https://doi.org/10.3174/ajnr.A5256

    Article  CAS  PubMed  Google Scholar 

  12. Bland JM, Altman DG (1986) Statistical methods for assessing agreement between two methods of clinical measurement. Lancet 1(8476):307–310

    Article  CAS  Google Scholar 

  13. Lin LI (1989) A concordance correlation coefficient to evaluate reproducibility. Biometrics 45(1):255–268

    Article  CAS  Google Scholar 

  14. Carrasco JL, King TS, Chinchilli VM (2009) The concordance correlation coefficient for repeated measures estimated by variance components. J Biopharm Stat 19(1):90–105. https://doi.org/10.1080/10543400802527890

    Article  PubMed  Google Scholar 

  15. Carrasco JL, Phillips BR, Puig-Martinez J, King TS, Chinchilli VM (2013) Estimation of the concordance correlation coefficient for repeated measures using SAS and R. Comput Methods Programs Biomed 109(3):293–304. https://doi.org/10.1016/j.cmpb.2012.09.002

    Article  PubMed  Google Scholar 

  16. Maeda AK, Aguiar LR, Martins C, Bichinho GL, Gariba MA (2013) Hematoma volumes of spontaneous intracerebral hemorrhage: the ellipse (ABC/2) method yielded volumes smaller than those measured using the planimetric method. Arq Neuropsiquiatr 71(8):540–544. https://doi.org/10.1590/0004-282X20130084

    Article  PubMed  Google Scholar 

  17. Sheth KN, Cushing TA, Wendell L et al (2010) Comparison of hematoma shape and volume estimates in warfarin versus non-warfarin-related intracerebral hemorrhage. Neurocrit Care 12(1):30–34. https://doi.org/10.1007/s12028-009-9296-7

    Article  PubMed  PubMed Central  Google Scholar 

  18. Huttner HB, Steiner T, Hartmann M et al (2006) Comparison of ABC/2 estimation technique to computer-assisted planimetric analysis in warfarin-related intracerebral parenchymal hemorrhage. Stroke 37(2):404–408. https://doi.org/10.1161/01.STR.0000198806.67472.5c

    Article  PubMed  Google Scholar 

  19. Divani AA, Majidi S, Luo X et al (2011) The ABCs of accurate volumetric measurement of cerebral hematoma. Stroke 42(6):1569–1574. https://doi.org/10.1161/STROKEAHA.110.607861

    Article  PubMed  Google Scholar 

  20. Sreenivasan SA, Madhugiri VS, Sasidharan GM, Kumar RV (2016) Measuring glioma volumes: a comparison of linear measurement based formulae with the manual image segmentation technique. J Cancer Res Ther 12(1):161–168. https://doi.org/10.4103/0973-1482.153999

    Article  CAS  PubMed  Google Scholar 

  21. Dirks MS, Butman JA, Kim HJ et al (2012) Long-term natural history of neurofibromatosis type 2-associated intracranial tumors. J Neurosurg 117(1):109–117. https://doi.org/10.3171/2012.3.JNS111649

    Article  PubMed  PubMed Central  Google Scholar 

  22. Kasuya H, Kubo O, Tanaka M, Amano K, Kato K, Hori T (2006) Clinical and radiological features related to the growth potential of meningioma. Neurosurg Rev 29(4):293–296. https://doi.org/10.1007/s10143-006-0039-3. (discussion 296–7)

    Article  PubMed  PubMed Central  Google Scholar 

  23. Kuratsu J, Kochi M, Ushio Y (2000) Incidence and clinical features of asymptomatic meningiomas. J Neurosurg 92(5):766–770. https://doi.org/10.3171/jns.2000.92.5.0766

    Article  CAS  PubMed  Google Scholar 

  24. Alva S, Eisenberg D, Duffy A, Roberts K, Israel G, Bell R (2008) Virtual three-dimensional computed tomography assessment of the gastric pouch following laparoscopic roux-Y gastric bypass. Obes Surg 18(4):364–366. https://doi.org/10.1007/s11695-008-9438-6

    Article  PubMed  Google Scholar 

  25. Bendon CL, Sheerin FB, Wall SA, Johnson D (2014) The relationship between scaphocephaly at the skull vault and skull base in sagittal synostosis. J Craniomaxillofac Surg 42(3):245–249. https://doi.org/10.1016/j.jcms.2013.05.009

    Article  PubMed  Google Scholar 

  26. Davies RS, Abdelhamid M, Vohra RK, Bradbury AW, Adam DJ (2012) The relationship between aortic aneurysm sac thrombus volume on coagulation, fibrinolysis and platelet activity. Thromb Res 130(3):463–466. https://doi.org/10.1016/j.thromres.2012.03.018

    Article  CAS  PubMed  Google Scholar 

  27. Wyss TR, Dick F, England A, Brown LC, Rodway AD, Greenhalgh RM (2009) Three-dimensional imaging core laboratory of the endovascular aneurysm repair trials: validation of methodology. Eur J Vasc Endovasc Surg 38(6):724–731. https://doi.org/10.1016/j.ejvs.2009.09.007

    Article  CAS  PubMed  Google Scholar 

  28. Yeung KK, van der Laan MJ, Wever JJ, van Waes PF, Blankensteijn JD (2003) New post-imaging software provides fast and accurate volume data from CTA surveillance after endovascular aneurysm repair. J Endovasc Ther 10(5):887–893. https://doi.org/10.1177/152660280301000507

    Article  PubMed  Google Scholar 

  29. Day NJ, Earnshaw D, Salazar-Ferrer P, Walsh CJ (2013) Preoperative mapping of fistula-in-ano: a new three-dimensional MRI-based modelling technique. Colorectal Dis 15(11):e699–e701. https://doi.org/10.1111/codi.12438

    Article  CAS  PubMed  Google Scholar 

  30. de Jonge GJ, van Ooijen PM, Overbosch J, Gueorguieva AL, Janssen-van der Weide MC, Oudkerk M. Comparison of (semi-)automatic and manually adjusted measurements of left ventricular function in dual source computed tomography using three different software tools. Int J Cardiovasc Imaging 2011;27(6):787-794. https://doi.org/10.1007/s10554-010-9727-8

    Article  PubMed  Google Scholar 

  31. Gaia BF, Pinheiro LR, Umetsubo OS, Costa FF, Cavalcanti MG (2013) Comparison of precision and accuracy of linear measurements performed by two different imaging software programs and obtained from 3D-CBCT images for le fort I osteotomy. Dentomaxillofac Radiol 42(5):20120178. https://doi.org/10.1259/dmfr.20120178

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  32. Gaia BF, Pinheiro LR, Umetsubo OS, Costa FF, Cavalcanti MG (2014) Validity of three-dimensional computed tomography measurements for le fort I osteotomy. Int J Oral Maxillofac Surg 43(2):197–203. https://doi.org/10.1016/j.ijom.2013.06.005

    Article  CAS  PubMed  Google Scholar 

  33. Perkins JA, Sidhu M, Manning SC, Ghioni V, Sze R (2005) Three-dimensional CT angiography imaging of vascular tumors of the head and neck. Int J Pediatr Otorhinolaryngol 69(3):319–325

    Article  Google Scholar 

  34. Greess H, Nomayr A, Tomandl B et al (2000) 2D and 3D visualisation of head and neck tumours from spiral-CT data. Eur J Radiol 33(3):170–177

    Article  CAS  Google Scholar 

  35. Kwon J, Barrera JE, Jung TY, Most SP (2009) Measurements of orbital volume change using computed tomography in isolated orbital blowout fractures. Arch Facial Plast Surg 11(6):395–398. https://doi.org/10.1001/archfacial.2009.77

    Article  PubMed  Google Scholar 

  36. Richard MJ, Morris C, Deen BF, Gray L, Woodward JA (2009) Analysis of the anatomic changes of the aging facial skeleton using computer-assisted tomography. Ophthal Plast Reconstr Surg 25(5):382–386. https://doi.org/10.1097/IOP.0b013e3181b2f766

    Article  PubMed  Google Scholar 

  37. Wang H, Li W, He H, Luo L, Chen C, Guo Y (2013) 320-detector row CT angiography for detection and evaluation of intracranial aneurysms: comparison with conventional digital subtraction angiography. Clin Radiol 68(1):e15–e20. https://doi.org/10.1016/j.crad.2012.09.001

    Article  CAS  PubMed  Google Scholar 

  38. Wilson DO, Ryan A, Fuhrman C et al (2012) Doubling times and CT screen-detected lung cancers in the pittsburgh lung screening study. Am J Respir Crit Care Med 185(1):85–89. https://doi.org/10.1164/rccm.201107-1223OC

    Article  PubMed  PubMed Central  Google Scholar 

  39. Shah GD, Kesari S, Xu R et al (2006) Comparison of linear and volumetric criteria in assessing tumor response in adult high-grade gliomas. Neuro Oncol 8(1):38–46

    Article  Google Scholar 

  40. Greenberg MS. Handbook of neurosurgery, 8th edn. New York: Thieme. c2016. Chapter 42, Meningiomas; pp 690–700.

Download references

Acknowledgements

Services in support of the research project were generated by the VCU Massey Cancer Center Biostatistics Shared Resource, supported, in part, with funding from NIH-NCI Cancer Center Support Grant P30 CA016059.

Author information

Authors and Affiliations

Authors

Corresponding author

Correspondence to William C. Broaddus.

Ethics declarations

Conflict of interest

The authors declare that they have no conflict of interest.

Ethical approval

All procedures performed in studies involving human participants were in accordance with the ethical standards of the institutional and/or national research committee and with the 1964 Helsinki declaration and its later amendments or comparable ethical standards. This article does not contain any studies with animals performed by any of the authors.

Additional information

Publisher’s Note

Springer Nature remains neutral with regard to jurisdictional claims in published maps and institutional affiliations.

Rights and permissions

Reprints and permissions

About this article

Check for updates. Verify currency and authenticity via CrossMark

Cite this article

Opalak, C.F., Parry, M., Rock, A.K. et al. Comparison of ABC/2 estimation and a volumetric computerized method for measurement of meningiomas using magnetic resonance imaging. J Neurooncol 144, 275–282 (2019). https://doi.org/10.1007/s11060-019-03205-z

Download citation

  • Received:

  • Accepted:

  • Published:

  • Issue Date:

  • DOI: https://doi.org/10.1007/s11060-019-03205-z

Keywords

Navigation