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Building Three-Dimensional Intracranial Aneurysm Models from 3D-TOF MRA: a Validation Study

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Abstract

To create realistic three-dimensional (3D) vascular models from 3D time-of-flight magnetic resonance angiography (3D-TOF MRA) of an intracranial aneurysm (IA). Thirty-two IAs in 31 patients were printed using 3D-TOF MRA source images from polylactic acid (PLA) raw material. Two observers measured the maximum IA diameter at the longest width twice separately. A total mean of four measurements as well as each observer’s individual average MRA lengths were calculated. After printing, 3D-printed anatomic models (PAM) underwent computed tomography (CT) acquisition and each observer measured them using the same algorithm as applied to MRA. Inter- and intra-observer consistency for the MRA and CT measurements were analyzed using the intraclass correlation coefficient (ICC) and a Bland-Altman plot. The mean maximum aneurysm diameter obtained from four MRA evaluations was 8.49 mm, whereas it was 8.83 mm according to the CT 3D PAM measurement. The Wilcoxon test revealed slightly larger mean CT 3D PAM diameters than the MRA measurements. The Spearman’s correlation test yielded a positive correlation between MRA and CT lengths of 3D PAMs. Inter and intra-observer consistency were high in consecutive MRA and CT measurements. According to Bland-Altman analyses, the aneurysmal dimensions obtained from CT were higher for observer 1 and observer 2 (a mean of 0.32 mm and 0.35 mm, respectively) compared to the MRA measurements. CT dimensions were slightly overestimated compared to MRA measurements of the created models. We believe the discrepancy may be related to the Laplacian algorithm applied for surface smoothing and the high slice thickness selection that was used. However, ICC provided high consistency and reproducibility in our cohort. Therefore, it is technically possible to produce 3D intracranial aneurysm models from 3D-TOF MRA images.

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References

  1. AHA aneurysms description. What you should know about cerebral aneurysms. Cited April 2018. Available from: https://www.strokeassociation.org/en/about-stroke/types-of-stroke/hemorrhagic-strokes-bleeds/what-you-should-know-about-cerebral-aneurysms

  2. Fifi JT, Meyers PM, Lavine SD, Cox V, Silverberg L, Mangla S, Pile-Spellman J: Complications of modern diagnostic cerebral angiography in an academic medical center. J Vasc Interv Radiol 20:442–447, 2009

    Article  Google Scholar 

  3. Wurm G, Tomancok B, Pogady P, Holl K, Trenkler J: Cerebrovascular stereolithographic biomodeling for aneurysm surgery. Technical note. J Neurosurg 100:139–145, 2004

    Article  Google Scholar 

  4. Wurm G, Lehner M, Tomancok B, Kleiser R, Nussbaumer K: Cerebrovascular biomodeling for aneurysm surgery: simulation-based training by means of rapid prototyping technologies. Surg Innov 18:294–306, 2011

    Article  Google Scholar 

  5. Kimura T, Morita A, Nishimura K, Aiyama H, Itoh H, Fukaya S, Sora S, Ochiai C: Simulation of and training for cerebral aneurysm clipping with 3-dimensional models. Neurosurgery 65:719–725, 2009

    Article  Google Scholar 

  6. Wang L, Ye X, Hao Q, Chen Y, Chen X, Wang H, Wang R, Zhao Y, Zhao J: Comparison of two three-dimensional printed models of complex intracranial aneurysms for surgical simulation. World Neurosurg 103:671–679, 2017

    Article  Google Scholar 

  7. Leal A, Souza M, Nohama P: Additive manufacturing of 3D biomodels as aadjuvant in intracranial aneurysm clipping. Artif Organs 43:E9–E15, 2019

    Article  Google Scholar 

  8. Wang JL, Yuan ZG, Qian GL, Bao WQ, Jin GL: 3D printing of intracranial aneurysm based on intracranial digital subtraction angiography and its clinical application. Medicine (Baltimore) 97:e11103, 2018

    Article  Google Scholar 

  9. Zhou LQ, Lou MW, Chen GC, Jiu ZS, Shen YX, Lu L: Value of 640-slice 3D CT angiography plus 3D printing for improving surgeries for intracranial aneurysms. Nan Fang Yi Ke Da Xue Xue Bao 37:1222–1227, 2017

    PubMed  Google Scholar 

  10. Mashiko T, Kaneko N, Konno T, Otani K, Nagayama R, Watanabe E: Training in cerebral aneurysm clipping using self-made 3-dimensional models. J Surg Educ 74:681–689, 2017

    Article  Google Scholar 

  11. Fedorov A, Beichel R, Kalpathy-Cramer J, Finet J, Fillion-Robin J-C, Pujol S: 3D slicer as an image computing platform for the quantitative imaging network. Magn Reson Imaging 30:1323–1341, 2012

    Article  Google Scholar 

  12. Maleike D, Nolden M, Meinzer HP, Wolf I: Interactive segmentation framework of the medical imaging interaction toolkit. Comput Methods Programs Biomed 96:72–83, 2009

    Article  CAS  Google Scholar 

  13. Parmar C, Rios Velazquez E, Leijenaar R, Jermoumi M, Carvalho S, Mak RH, Mitra S, Shankar BU, Kikinis R, Haibe-Kains B, Lambin P, Aerts HJ: Robust radiomics feature quantification using semiautomatic volumetric segmentation. PLoS One 9:e102107, 2014

    Article  Google Scholar 

  14. Steiner T, Juvela S, Unterberg A, Jung C, Forsting M, Rinkel G: European stroke organization guidelines for the management of intracranial aneurysms and subarachnoid haemorrhage. Cerebrovasc Dis 35(2):93–112, 2013

    Article  Google Scholar 

  15. Adams WM, Laitt RD, Jackson A: The role of MR angiography in the pretreatment assessment of intracranial aneurysms: a comparative study. Am J Neuroradiol 21:1618–1628, 2000

    CAS  PubMed  Google Scholar 

  16. Hoh BL, Cheung AC, Rabinov JD, Pryor JC, Carter BS, Ogilvy CS: Results of a prospective protocol of computed tomographic angiography in place of catheter angiography as the only diagnostic and pretreatment planning study for cerebral aneurysms by a combined neurovascular team. Neurosurgery 54(6):1329–1342, 2004

    Article  Google Scholar 

  17. Mallouhi A, Felber S, Chemelli A, Dessl A, Auer A, Schocke M, Jaschke WR, Waldenberger P: Detection and characterization of intracranial aneurysms with MR angiography: comparison of volume-rendering and maximum-intensity-projection algorithms. Am J Roentgenol 180:55–64, 2003

    Article  Google Scholar 

  18. Sailer A, Wagemans B, Nelemans P, de Graaf R, van Zwam W: Diagnosing intracranial aneurysms with MR angiography: systematic review and meta-analysis. Stroke 45:119–126, 2014

    Article  Google Scholar 

  19. Pierot L, Portefaix C, Rodriguez-Régent C, Gallas S, Meder J-F, Oppenheim C: Role of MRA in the detection of intracranial aneurysm in the acute phase of subarachnoid hemorrhage. J Neuroradiol 40(11):204–210, 2013

    Article  Google Scholar 

  20. HaiFeng L, YongSheng X, YangQin X, Yu D, ShuaiWen W, XingRu L, JunQiang L: Diagnostic value of 3D time-of-flight magnetic resonance angiography for detecting intracranial aneurysm: a meta-analysis. Neuroradiology 59:1083–1092, 2017

    Article  Google Scholar 

  21. Torres IO, De Luccia N: A simulator for training in endovascular aneurysm repair: the use of three dimensional printers. Eur J Vasc Endovasc Surg 54:247–253, 2017

    Article  CAS  Google Scholar 

  22. Shibata E, Takao H, Amemiya S, Ohtomo K: 3D-printed visceral aneurysm models based on ct data for simulations of endovascular embolization: evaluation of size and shape accuracy. Am J Roentgenol 209:243–247, 2017

    Article  Google Scholar 

  23. Wang L, Ye X, Hao Q, Ma L, Chen X, Wang H, Zhao Y: Three-dimensional intracranial middle cerebral artery aneurysm models for aneurysm surgery and training. J Clin Neurosci 50:77–82, 2018

    Article  CAS  Google Scholar 

  24. Liu T, Chen M, Song Y, Li H, Lu B: Quality improvement of surface triangular mesh using a modified Laplacian smoothing approach avoiding intersection. Shi Y, editor. PLoS One 12:e0184206, 2017

    Article  Google Scholar 

  25. Despotović I, Goossens B, Philips W: MRI segmentation of the human brain: challenges, methods, and applications. Comput Math Methods Med 2015. https://doi.org/10.1155/2015/450341

    Article  Google Scholar 

  26. George E, Liacouras P, Rybicki FJ, Mitsouras D: Measuring and establishing the accuracy and reproducibility of 3D printed medical models. Radiographics 37:1424–1450, 2017

    Article  Google Scholar 

  27. Kim HJ, Yoon DY, Kim ES, Lee HJ, Jeon HJ, Lee JY, Cho BM: Intraobserver and interobserver variability in CT angiography and MR angiography measurements of the size of cerebral aneurysms. Neuroradiology 59:491–497, 2017

    Article  Google Scholar 

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Authors and Affiliations

  1. Department of Radiology, University of Health Sciences Bozyaka Education and Training Hospital, Izmir, Turkey

    Turker Acar & Ali Murat Koc

  2. Department of Anatomy Digital Imaging and 3D Modelling Laboratory, Faculty of Medicine, Ege University School of Medicine, TR-35100, Izmir, Turkey

    Turker Acar, Asli Beril Karakas, Mehmet Asim Ozer & Figen Govsa

  3. Department of Radiology, University of Ottawa Faculty of Medicine and The Ottawa Hospital Research, Institute, Ottawa, Ontario, Canada

    Turker Acar

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  1. Turker Acar
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  2. Asli Beril Karakas
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  3. Mehmet Asim Ozer
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  4. Ali Murat Koc
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  5. Figen Govsa
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Contributions

Study design: TA, MAO

Data assembly: ABK

Data analysis: MAO, AMK

Final approval of manuscript: TA, FG

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Correspondence to Figen Govsa.

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Acar, T., Karakas, A.B., Ozer, M.A. et al. Building Three-Dimensional Intracranial Aneurysm Models from 3D-TOF MRA: a Validation Study. J Digit Imaging 32, 963–970 (2019). https://doi.org/10.1007/s10278-019-00256-6

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  • DOI: https://doi.org/10.1007/s10278-019-00256-6

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