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Molecular Imaging and Biology
Published in: Molecular Imaging and Biology 3/2016

01-06-2016 | Research Article

Semi-Automated Volumetric and Morphological Assessment of Glioblastoma Resection with Fluorescence-Guided Surgery

Authors: J. Scott Cordova, Saumya S. Gurbani, Chad A. Holder, Jeffrey J. Olson, Eduard Schreibmann, Ran Shi, Ying Guo, Hui-Kuo G. Shu, Hyunsuk Shim, Costas G. Hadjipanayis

Published in: Molecular Imaging and Biology | Issue 3/2016

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Abstract

Purpose

Glioblastoma (GBM) neurosurgical resection relies on contrast-enhanced MRI-based neuronavigation. However, it is well-known that infiltrating tumor extends beyond contrast enhancement. Fluorescence-guided surgery (FGS) using 5-aminolevulinic acid (5-ALA) was evaluated to improve extent of resection (EOR) of GBMs. Preoperative morphological tumor metrics were also assessed.

Procedures

Thirty patients from a phase II trial evaluating 5-ALA FGS in newly diagnosed GBM were assessed. Tumors were segmented preoperatively to assess morphological features as well as postoperatively to evaluate EOR and residual tumor volume (RTV).

Results

Median EOR and RTV were 94.3 % and 0.821 cm3, respectively. Preoperative surface area to volume ratio and RTV were significantly associated with overall survival, even when controlling for the known survival confounders.

Conclusions

This study supports claims that 5-ALA FGS is helpful at decreasing tumor burden and prolonging survival in GBM. Moreover, morphological indices are shown to impact both resection and patient survival.
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Literature
1.
Bloch O, Han SJ, Cha S et al (2012) Impact of extent of resection for recurrent glioblastoma on overall survival: clinical article. J Neurosurg 117:1032–1038CrossRefPubMed
2.
Stummer W, Meinel T, Ewelt C et al (2012) Prospective cohort study of radiotherapy with concomitant and adjuvant temozolomide chemotherapy for glioblastoma patients with no or minimal residual enhancing tumor load after surgery. J Neurooncol 108:89–97CrossRefPubMedPubMedCentral
3.
4.
Chaichana KL, Cabrera-Aldana EE, Jusue-Torres I et al (2014) When gross total resection of a glioblastoma is possible, how much resection should be achieved? World Neurosurg 82:e257–265CrossRefPubMed
5.
Chaichana KL, Jusue-Torres I, Navarro-Ramirez R et al (2014) Establishing percent resection and residual volume thresholds affecting survival and recurrence for patients with newly diagnosed intracranial glioblastoma. Neurol Oncol 16:113–122CrossRef
6.
Lacroix M, Abi-Said D, Fourney DR et al (2001) A multivariate analysis of 416 patients with glioblastoma multiforme: prognosis, extent of resection, and survival. J Neurosurg 95:190–198CrossRefPubMed
7.
Sanai N, Berger MS (2008) Glioma extent of resection and its impact on patient outcome. Neurosurgery 62:753–764CrossRefPubMed
8.
Sanai N, Polley MY, McDermott MW et al (2011) An extent of resection threshold for newly diagnosed glioblastomas. J Neurosurg 115:3–8CrossRefPubMed
9.
Vogelbaum MA, Jost S, Aghi MK et al (2012) Application of novel response/progression measures for surgically delivered therapies for gliomas: Response Assessment in Neuro-Oncology (RANO) Working Group. Neurosurgery 70:234–243CrossRefPubMed
10.
Kubben PL, Scholtes F, Schijns OE et al (2014) Intraoperative magnetic resonance imaging versus standard neuronavigation for the neurosurgical treatment of glioblastoma: a randomized controlled trial. Surg Neurol Int 5:70–79PubMedPubMedCentral
11.
Hadjipanayis CG, Widhalm G, Stummer W (2015) What is the surgical benefit of utilizing 5-aminolevulinic acid for fluorescence-guided surgery of malignant gliomas? Neurosurgery
12.
Hinnen P, de Rooij FW, van Velthuysen ML et al (1998) Biochemical basis of 5-aminolaevulinic acid-induced protoporphyrin IX accumulation: a study in patients with (pre)malignant lesions of the oesophagus. Br J Cancer 78:679–682CrossRefPubMedPubMedCentral
13.
Stummer W, Stocker S, Novotny A et al (1998) In vitro and in vivo porphyrin accumulation by C6 glioma cells after exposure to 5-aminolevulinic acid. J Photochem Photobiol B 45:160–169CrossRefPubMed
14.
Gibson SL, Havens JJ, Metz L, Hilf R (2001) Is δ-aminolevulinic acid dehydratase rate limiting in heme biosynthesis following exposure of cells to δ-aminolevulinic acid? Photochem Photobiol 73:312–317CrossRefPubMed
15.
Collaud S, Juzeniene A, Moan J, Lange N (2004) On the selectivity of 5-aminolevulinic acid-induced protoporphyrin IX formation. Curr Med Chem Anticancer Agents 4:301–316CrossRefPubMed
16.
Novotny A, Xiang J, Stummer W et al (2000) Mechanisms of 5-aminolevulinic acid uptake at the choroid plexus. J Neurochem 75:321–328CrossRefPubMed
17.
18.
Olivo M, Wilson BC (2004) Mapping ALA-induced PPIX fluorescence in normal brain and brain tumour using confocal fluorescence microscopy. Int J Oncol 25:37–45PubMed
19.
Rud E, Gederaas O, Hogset A, Berg K (2000) 5-aminolevulinic acid, but not 5-aminolevulinic acid esters, is transported into adenocarcinoma cells by system BETA transporters. Photochem Photobiol 71:640–647CrossRefPubMed
20.
Ennis SR, Novotny A, Xiang J et al (2003) Transport of 5-aminolevulinic acid between blood and brain. Brain Res 959:226–234CrossRefPubMed
21.
Zhao SG, Chen XF, Wang LG et al (2013) Increased expression of ABCB6 enhances protoporphyrin IX accumulation and photodynamic effect in human glioma. Ann Surg Oncol 20:4379–4388CrossRefPubMed
22.
23.
Sanai N (2012) Emerging operative strategies in neurosurgical oncology. Curr Opin Neurol 25:756–766CrossRefPubMed
24.
Della Puppa A, De Pellegrin S, d’Avella E et al (2013) 5-aminolevulinic acid (5-ALA) fluorescence guided surgery of high-grade gliomas in eloquent areas assisted by functional mapping. Our experience and review of the literature. Acta Neurochir (Wien) 155:965–972CrossRef
25.
Schucht P, Beck J, Abu-Isa J et al (2012) Gross total resection rates in contemporary glioblastoma surgery: results of an institutional protocol combining 5-aminolevulinic acid intraoperative fluorescence imaging and brain mapping. Neurosurgery 71:927–935CrossRefPubMed
26.
Schucht P, Seidel K, Beck J et al (2014) Intraoperative monopolar mapping during 5-ALA-guided resections of glioblastomas adjacent to motor eloquent areas: evaluation of resection rates and neurological outcome. Neurosurg Focus 37:E16–24CrossRefPubMed
27.
Keles GE, Chang EF, Lamborn KR et al (2006) Volumetric extent of resection and residual contrast enhancement on initial surgery as predictors of outcome in adult patients with hemispheric anaplastic astrocytoma. J Neurosurg 105:34–40CrossRefPubMed
28.
Pope WB, Sayre J, Perlina A et al (2005) MR imaging correlates of survival in patients with high-grade gliomas. AJNR Am J Neuroradiol 26:2466–2474PubMed
29.
Grabowski MM, Recinos PF, Nowacki AS et al (2014) Residual tumor volume versus extent of resection: predictors of survival after surgery for glioblastoma. J Neurosurg 121:1115–1123CrossRefPubMed
30.
Stummer W, Pichlmeier U, Meinel T et al (2006) Fluorescence-guided surgery with 5-aminolevulinic acid for resection of malignant glioma: a randomised controlled multicentre phase III trial. Lancet Oncol 7:392–401CrossRefPubMed
31.
Hadjipanayis CG, Jiang H, Roberts DW, Yang L (2011) Current and future clinical applications for optical imaging of cancer: from intraoperative surgical guidance to cancer screening. Semin Oncol 38:109–118CrossRefPubMedPubMedCentral
32.
Van Meir EG, Hadjipanayis CG, Norden AD et al (2010) Exciting new advances in neuro-oncology: the avenue to a cure for malignant glioma. CA Cancer J Clin 60:166–193CrossRefPubMedPubMedCentral
33.
Barbosa BJ, Mariano ED, Batista CM et al (2015) Intraoperative assistive technologies and extent of resection in glioma surgery: a systematic review of prospective controlled studies. Neurosurg Rev 38:217–226CrossRefPubMed
34.
Stummer W, Novotny A, Stepp H et al (2000) Fluorescence-guided resection of glioblastoma multiforme by using 5-aminolevulinic acid-induced porphyrins: a prospective study in 52 consecutive patients. J Neurosurg 93:1003–1013CrossRefPubMed
35.
van den Bent MJ, Vogelbaum MA, Wen PY et al (2009) End point assessment in gliomas: novel treatments limit usefulness of classical Macdonald’s Criteria. J Clin Oncol 27:2905–2908CrossRefPubMedPubMedCentral
36.
Wen PY, Macdonald DR, Reardon DA et al (2010) Updated response assessment criteria for high-grade gliomas: response assessment in neuro-oncology working group. J Clin Oncol 28:1963–1972CrossRefPubMed
37.
Hughes I, Hase T (2010) Error propagation. In: measurements and their uncertainties: a practical guide to modern error analysis. New York: Oxford University Press Inc, New York, pp 37–52
38.
Macdonald DR, Cascino TL, Schold SC Jr, Cairncross JG (1990) Response criteria for phase II studies of supratentorial malignant glioma. J Clin Oncol 8:1277–1280PubMed
39.
40.
Gordillo N, Montseny E, Sobrevilla P (2013) State of the art survey on MRI brain tumor segmentation. Magn Reson Imaging 31:1426–1438CrossRefPubMed
41.
Bauer S, Wiest R, Nolte LP, Reyes M (2013) A survey of MRI-based medical image analysis for brain tumor studies. Phys Med Biol 58:R97–129CrossRefPubMed
42.
White DR, Houston AS, Sampson WF, Wilkins GP (1999) Intra- and interoperator variations in region-of-interest drawing and their effect on the measurement of glomerular filtration rates. Clin Nucl Med 24:177–181CrossRefPubMed
43.
Sorensen AG, Patel S, Harmath C et al (2001) Comparison of diameter and perimeter methods for tumor volume calculation. J Clin Oncol 19:551–557PubMed
44.
Chow DS, Qi J, Guo X et al (2014) Semiautomated volumetric measurement on postcontrast MR imaging for analysis of recurrent and residual disease in glioblastoma multiforme. AJNR Am J Neuroradiol 35:498–503CrossRefPubMed
45.
Cordova JS, Schreibmann E, Hadjipanayis CG et al (2014) Quantitative tumor segmentation for evaluation of extent of glioblastoma resection to facilitate multisite clinical trials. Transl Oncol 7:40–47CrossRefPubMedPubMedCentral
46.
Chang HH, Zhuang AH, Valentino DJ, Chu WC (2009) Performance measure characterization for evaluating neuroimage segmentation algorithms. Neuroimage 47:122–135CrossRefPubMed
47.
Collett D (2003) Strategy for model selection. In: Chatfield C, Lindsey J, Tanner M, Zidek J (eds) Modeling binary data. Chapman & Hall/CRC, Boca Raton, pp 91–97
48.
Orringer D, Lau D, Khatri S et al (2012) Extent of resection in patients with glioblastoma: limiting factors, perception of resectability, and effect on survival. J Neurosurg 117:851–859CrossRefPubMed
49.
Sanai N, Berger MS (2011) Extent of resection influences outcomes for patients with gliomas. Rev Neurol (Paris) 167:648–654CrossRef
50.
Paravati AJ, Heron DE, Landsittel D et al (2011) Radiotherapy and temozolomide for newly diagnosed glioblastoma and anaplastic astrocytoma: validation of radiation therapy oncology group-recursive partitioning analysis in the IMRT and temozolomide era. J Neurooncol 104:339–349CrossRefPubMedPubMedCentral
51.
Gutman DA, Cooper LA, Hwang SN et al (2013) MR imaging predictors of molecular profile and survival: multi-institutional study of the TCGA glioblastoma data set. Radiology 267:560–569CrossRefPubMedPubMedCentral
52.
Crawford FW, Khayal IS, McGue C et al (2009) Relationship of pre-surgery metabolic and physiological MR imaging parameters to survival for patients with untreated GBM. J Neurooncol 91:337–351CrossRefPubMedPubMedCentral
53.
Saraswathy S, Crawford FW, Lamborn KR et al (2009) Evaluation of MR markers that predict survival in patients with newly diagnosed GBM prior to adjuvant therapy. J Neurooncol 91:69–81CrossRefPubMedPubMedCentral
Metadata
Title
Semi-Automated Volumetric and Morphological Assessment of Glioblastoma Resection with Fluorescence-Guided Surgery
Authors
J. Scott Cordova
Saumya S. Gurbani
Chad A. Holder
Jeffrey J. Olson
Eduard Schreibmann
Ran Shi
Ying Guo
Hui-Kuo G. Shu
Hyunsuk Shim
Costas G. Hadjipanayis
Publication date
01-06-2016
Publisher
Springer US
Published in
Molecular Imaging and Biology / Issue 3/2016
Print ISSN: 1536-1632
Electronic ISSN: 1860-2002
DOI
https://doi.org/10.1007/s11307-015-0900-2

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