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Background:
Systematic Review

A Systematic Review of Amino Acid PET Imaging in Adult-Type High-Grade Glioma Surgery: A Neurosurgeon’s Perspective

by
Raffaele De Marco
1,
Alessandro Pesaresi
1,
Andrea Bianconi
1,*,
Michela Zotta
2,
Désirée Deandreis
2,
Giovanni Morana
3,
Pietro Zeppa
1,
Antonio Melcarne
1,
Diego Garbossa
1 and
Fabio Cofano
1
1
Neurosurgery Unit, Department of Neuroscience “Rita Levi Montalcini”, “Città della Salute e della Scienza” University Hospital, University of Turin, 10124 Turin, Italy
2
Nuclear Medicine Division, Department of Nuclear Medicine, “Città della Salute e della Scienza” University Hospital, University of Turin, 10124 Turin, Italy
3
Division of Neuroradiology, Department of Diagnostic Imaging and Radiotherapy, “Città della Salute e della Scienza” University Hospital, University of Turin, 10124 Turin, Italy
*
Author to whom correspondence should be addressed.
Cancers 2023, 15(1), 90; https://doi.org/10.3390/cancers15010090
Submission received: 30 September 2022 / Revised: 4 December 2022 / Accepted: 13 December 2022 / Published: 23 December 2022
(This article belongs to the Special Issue Management of Glioblastomas)
Browse Figure
Review Reports Versions Notes

Abstract

:

Simple Summary

Several advantages of molecular imaging, namely, positron emission tomography (PET), have been already described in different settings of glioma management. Particularly, the use of amino acidic radiotracers for PET imaging has gained favor for their added value in diagnosis, grading, guidance, and response to treatment and in order to rule out recurrences. Despite the meaning of the biologically active volume of the tumor, a PET-integrated resection of adult-type diffuse high-grade gliomas is not routinely performed, but it can represent a further perspective for neurosurgeons. A systematic review of the literature has been performed to investigate this topic with a precise focus on the neurosurgeon’s point of view presented, examining the reasons of its limited use in surgical practice and possible applications.

Abstract

Amino acid PET imaging has been used for a few years in the clinical and surgical management of gliomas with satisfactory results in diagnosis and grading for surgical and radiotherapy planning and to differentiate recurrences. Biological tumor volume (BTV) provides more meaningful information than standard MR imaging alone and often exceeds the boundary of the contrast-enhanced nodule seen in MRI. Since a gross total resection reflects the resection of the contrast-enhanced nodule and the majority of recurrences are at a tumor’s margins, an integration of PET imaging during resection could increase PFS and OS. A systematic review of the literature searching for “PET” [All fields] AND “glioma” [All fields] AND “resection” [All fields] was performed in order to investigate the diffusion of integration of PET imaging in surgical practice. Integration in a neuronavigation system and intraoperative use of PET imaging in the primary diagnosis of adult high-grade gliomas were among the criteria for article selection. Only one study has satisfied the inclusion criteria, and a few more (13) have declared to use multimodal imaging techniques with the integration of PET imaging to intentionally perform a biopsy of the PET uptake area. Despite few pieces of evidence, targeting a biologically active area in addition to other tools, which can help intraoperatively the neurosurgeon to increase the amount of resected tumor, has the potential to provide incremental and complementary information in the management of brain gliomas. Since supramaximal resection based on the extent of MRI FLAIR hyperintensity resulted in an advantage in terms of PFS and OS, PET-based biological tumor volume, avoiding new neurological deficits, deserves further investigation.

1. Introduction

Among adult-type high-grade gliomas, glioblastoma (GBM) IDH wildtype is the most common malignant brain tumor in neuro-oncology practice [1,2]. Maximal safe resection is the first-line treatment, followed by concomitant chemoradiotherapy (Stupp protocol [3]). Different studies have demonstrated the importance of the extent of resection (EOR) in terms of progression-free survival (PFS) and overall survival (OS) [4]. Generally, the extent of resection in newly diagnosed GBM aims to reach the contrast-enhanced borders of the lesion, which is defined in contrast-enhanced magnetic resonance imaging (ceMRI) [5]. Although there is no unique definition of gross total resection (GTR) [6], most studies report a complete removal of tumor at postoperative MRI stating contrast-enhanced tumor as a benchmark for GTR. This goal is affordable, taking advantage of different tools, such as fluorophores (i.e., sodium fluorescein and 5-aminolevulinic acid (5-ALA), which are the most used and validated) [7,8] or intraoperative imaging (i.e., neuronavigation system, intraoperative MRI (iMRI), intraoperative ultrasound (iOUS), and contrast-enhanced ultrasound (CE-US)) [9,10,11,12,13,14]. More recently, supratotal or supramaximal resection (SupTR) has proven to increase PFS and OS [15,16,17,18]. It is defined as complete removal of signal abnormalities beyond the contrast-enhanced borders of the tumor, and its rationale is in the assumption that glioma cells are infiltrative a priori [19,20]. Indeed, the majority of relapses are at a tumor’s margins [21,22]. Further signal abnormalities beyond the contrast-enhancing nodule include the T2-weighted hyperintensity seen at fluid-attenuated inversion recovery (FLAIR) MRI sequence [23] or the biologically active areas marked in positron emission tomography (PET). Few comparisons between MRI and different PET-based imaging techniques have revealed the presence of an active tumor beyond contrast-enhanced borders, and sometimes active regions could be even placed outside the T2/FLAIR hyperintensity [24]. Amino acid PET (AA-PET) imaging has emerged as a reliable imaging technique, in terms of diagnosis, histopathological correlation, surgical planning, and prognosis [25]. With increasing specificity and sensitivity compared with 18F-fluorodeoxyglucose (18F-FDG) and other conventional imaging, radiolabeled amino acid (i.e., [methyl-11C]-L-methionine (Met), O-(2-[18F]fluoroethyl)-L-tyrosine (FET), 18F-fluoro-L-dihydroxy-phenylalanine (FDOPA)) PET can depict the metabolic activity of gliomas, highlighting areas with a different radiotracer uptake—and theoretically with a different malignant potential—regardless of the blood–brain barrier impairment, adding further information on tumor extension [26,27].
The purpose of the current review is to investigate the role of amino acid PET specifically in improving the extent of the resection of high-grade gliomas and accordingly increasing PFS and OS.

2. Materials and Methods

A literature review was conducted in the PubMed database investigating the use of PET imaging as a guidance in glioma surgery using the PubMed database and PRISMA (Preferred Reporting Items for Systematic Reviews and Meta-analyses) recommendations. In order to include as many relevant articles as possible, there were no restrictions on the date of publication. The search terms used were “PET” AND “glioma” AND “resection”, including all fields. The literature was systematically reviewed by two independent reviewers (RDM and AP). All disagreements were resolved by further discussion with the senior author (FC).
The selection process was characterized by the following inclusion criteria: (1) availability of the manuscript in English or an English translation, (2) primary clinical studies investigating the use of PET imaging to guide intraoperatively high-grade glioma resection, and (3) a population >18 years old. All articles reviewed were also subject to the following exclusion criteria: (1) case reports, (2) reviews and preclinical studies, (3) biopsies, (4) preoperative characteristics resembling low-grade glioma (LGG) and/or histological confirmation of LGG, (5) studies involving pediatric patients, and (6) nonuse of PET imaging data in the neuronavigation system as guidance for surgical resection.
The systematic review followed the recommendations of the Preferred Reporting Items for Systematic Reviews and Meta-Analyses (PRISMA). The protocol has not been registered.

3. Results

The PubMed search yielded 276 results after confirming the absence of duplicates.
Out of the 276 unique papers, full-text analysis was performed for 143 articles. In most cases, PET imaging was used for assessing the extent of resection. In 15 articles, PET imaging was integrated in surgical planning, but only one article met both inclusion and exclusion criteria [28] (Figure 1: PRISMA Flowchart).
Indeed, a study conducted by Inoue et al. [28] considered only adults affected by newly diagnosed high-grade glioma (WHO 2021 grade 4) that underwent surgical resection with the integration and fusion of Met-PET imaging during surgery. They demonstrated the presence of glioma stem cells beyond the border of the MRI enhancing nodule. Furthermore, an important part of the biologically active tumor, highlighted with the PET imaging technique, was located outside the borders defined by gadolinium. Specifically, an analysis of a different tumor-to-contralateral normal brain tissue ratio (TNR), from 1.2 to >2.0, found that the threshold at 1.4 was always beyond the borders of the MRI contrast-enhanced nodule, but, at the same time, in nine cases out of 10, was smaller than the area with FLAIR hyperintensity. A pathological investigation of tumor pieces obtained by these different areas confirmed the biological significance in terms of proliferative index (ki-67 of 23.6%, range of 5.8–68.3% vs. 39.3%, range of 14.9–68.0%, which was the one tissue obtained by the highest contrast-enhanced and highest SUV-PET-positive areas).
Conversely, the auxiliary use of PET imaging and its integration in the neuronavigation system as a tool to localize the bioptic area and to define the borders in primary diagnosed glioma was described in 15 articles (Table 1) [29,30,31,32,33,34,35,36,37,38,39,40,41,42,43].
Sample size, patient demographics (i.e., sex and age), extent of resection, overall survival, and progression-free survival were the information retrieved from the selected article (Table 2). An eligible article was excluded due to the inclusion of children in their study population [45].

4. Discussion

The results show a paucity of studies in which PET imaging was integrated in the surgical planning and used to guide resection beyond the contrast-enhanced borders of conventional MRI. Furthermore, a great discrepancy and heterogeneity among available articles was observed, both in the design and in the aim of the studies.
In the diagnostic setting, different reports have mainly correlated PET tracer uptake in glioma tissue with its biological characteristics, namely, cell density [47,48,49,50]. This correlation has been demonstrated to be stronger than that seen intraoperatively with 5-ALA [36,51].
The most used radiolabeled amino acid PET imaging shares the same mechanism to enter inside tumor cells: L-amino acid transporters (LAT) are broadly expressed in tumor tissue but not in normal brain tissue, increasing the tumor-to-background contrast compared with 2-deoxy-2-[18F] fluoro-D-glucose (FDG)-PET, which presents a high physiological brain uptake [52]. Specifically, LAT1 is the main transporter type for Met, FET, and FDOPA [53,54,55]. Once inside glioma cells, the metabolic pathway differs for each one of them, opening on different possibilities of clinical investigations and applications [56].
In addition to the specific molecule used as radiopharmaceutical, the radiolabeling process and the involved radioisotope are different and have an impact on image acquisition and availability. In fact, 11C amino acids show a short half-life (only 20 min) compared with 18F radiolabeled amino acids (110 min), needing an on-site cyclotron [56] and limiting their use to a few centers. The introduction of 18F radiolabeled amino acids in brain tumors—especially in glioma—busted an increasing interest in these radiotracers with some advantages compared with Met-PET imaging [56]. Indeed, a rapid research on PubMed for “FET-PET AND Glioma” returned nearly 200 articles in the period between 2015 and 2020. Although with less impact compared with FET-PET, 18F-DOPA PET has gained interest in adult and pediatric glioma research in the last decade [57,58,59,60,61,62,63].
All amino acids have shown to offer additional information to conventional imaging, but only few studies have compared them directly [64,65,66]. Beyond its role in diagnosis [44,67] and eventually in grading [52,63,68,69,70,71], AA-PET imaging can offer information on a tumor’s extension in a more specific and sensitive way than structural MRI with gadolinium and FLAIR sequence as well [24]. Furthermore, this additional information could result in paramount importance for surgical planning when a significant part of the tumor lacks the contrast enhancement [72,73,74].
Indeed, the calculation of biological tumor volume (BTV) could detect more meaningful areas (in terms of pathological diagnosis) when a biopsy is planned or when MRI information is not sufficient for safe resection, either because the MRI borders reach eloquent brain regions or because it might correspond to scar tissue in case of glioma recurrence [36,75]. Furthermore, the integration of AA-PET imaging for surgical planning or for biopsy is recommended by the current guidelines [26,27].
In detail, AA-PET imaging has been demonstrated to more accurately identify in-filtrating regions of tumor extending beyond the MRI contrast-enhancing lesion, delineating significantly larger tumor volumes, and to better define tumor boundaries within nonspecific regions of MRI T2/FLAIR signal abnormality (infiltrative disease vs. vasogenic edema) [76]. Additionally, it provides further insights regarding tumor heterogeneity, biological activity, or aggressiveness of the disease [77].
Most of the studies that have analyzed the integration of PET imaging in the operating room focused on the histopathological validation of PET findings. Conversely, a pioneering work by Pirotte et al. demonstrated an advantage of PET-guided resection for grade 3 and 4 gliomas [45]: a statistically significant difference of 14.9 months benefited those patients without postoperative PET tracer uptake.
Although a thoroughly demonstrated association between PET tracer uptake (Met-PET) and viable glial cells has been identified in the core of the tumor, the same correlation has not always preserved at the tumor border and especially at tumor-infiltrated areas. Other techniques have been proposed to increase the reliability of PET imaging in MRI nonenhanced areas (beyond the contrast-enhanced nodule) [78,79,80].
Inoue et al. [28] focused on the tumor-to-contralateral normal brain tissue ratio (TNR) to evaluate the metabolic activity of GBM. Using Met-PET, they demonstrated the presence of glioma stem-like cells at TNR 1.4 of the tracer uptake, beyond the contrast-enhanced borders of standard MRI. Specifically, dividing GBMs in three subtypes (A, B, and C types) on the basis of radiological features, they found a better progression-free survival and overall survival for those subtypes where the difference between PET-based borders’ evaluation (TNR of 1.4) and contrast-enhanced T1-weighted MRI imaging was low. Indeed, a GTR of contrast-enhanced borders as in the latter GBM subtype (namely, B subtype) was an indirect expression of meaningful PET radiotracer uptake area resection. Since most glioma recurrences occur at borders of the resected cavity, hypothesizing an origin of tumor recurrence from glioma stem-like cells, the surgical goal should seek these margins according to PET uptake when safe. However, the same limits should be used in the radiation treatment planning, as already proposed [81,82].
Nevertheless, the authors stressed the difficulty of safely performing a resection of this PET uptake area (characterized by TNR of 1.4), especially when the tumor arises near eloquent areas: the contemporary use of additional tools, such as intraoperative fluorophores and neuromonitoring, which enhances the information of a real-time image-guided navigation system, where both PET and MRI fusion images were used (i.e., echo-linked navigation and fence-post technique), allowed for obtaining a better outcome. From unpublished series, the median OS for patients where Met-PET imaging was integrated in the navigation system was of 21.6 months compared with 15.2 months where the same tools were used but without metabolic information. A similar improvement on survival was already reported for other series (which comprehended both children and adults and WHO grades III and IV), where PET imaging was integrated in surgical planning [45,83]. Even in the absence of an integrated PET imaging surgical procedure, a small postoperative BTV, more than GTR of the contrast-enhanced nodule, was associated with better rates of PFS and OS, without an increase in new neurological deficits [25].
A similar result was confirmed in a recent retrospective study where 30 patients with primary and recurrent WHO grade 3 and 4 gliomas were recruited [46] (this report was excluded due to the absence of a statement on the integration of PET imaging during resection). Patients with a primary diagnosed glioblastoma were 16 (overall 20). Performing an image analysis of preoperative MRI and FET-PET data, they found a BTV GTR in 20 patients, obtaining a statistically significant improvement in OS compared with the patients with PET residuals (19.3 vs. 13.7 months, p = 0.007), which remained significant in the group with a primary diagnosis of glioma (17.3 vs. 13.7 months, p = 0.048) and even for glioblastoma (15.1 vs. 13.6 months, p = 0.048).
Interestingly, Hirono et al. (this report was excluded for the same reason as above) analyzed retrospectively the survival benefit that should have been conferred by resecting additional tissue beyond contrast-enhanced borders that appeared to show Met-PET uptake. A resection beyond contrast-enhanced borders seen at standard MRI was considered a supratotal resection (SupTR). Among 30 patients with primary diagnosis of glioblastoma, they obtained 23 GTRs and 7 SupTRs. Twelve patients underwent awake craniotomy with cortical and subcortical direct electrical stimulation (DES), and remarkably, all SupTRs were registered in this group.
Although most studies have been conducted with Met-PET, other reports have shown that 18F radiolabeled amino acids (i.e., FET-PET and 18F-DOPA-PET) provided similar information in glioma patients [66,81]. Among Met, FET, and DOPA PET tracers, similar results in terms of accuracy have been reported regarding the ability to detect tumor boundary [66,84,85]. When compared with Met and FET, the main potential drawback of DOPA is its specific uptake in the striatum that may affect the ability to assess the involvement of the putamen and caudate nucleus [85,86]. On the other hand, DOPA uptake within the striatum gives the opportunity to further stratify tumoral uptake ratios through comparison with both the normal background levels and the striatum [87].
Another matter of research has been a possible link between AA-PET radiotracers and intraoperative fluorescent dyes. Indeed, a relationship between FET uptake and 5-ALA fluorescence has been demonstrated [88], and despite few described cases, FET uptake appeared to be more sensitive compared with intraoperative 5-ALA [34]. However, the absence of intraoperative fluorescence was related to low FET-PET uptake. The more fluorescing tissues was removed during surgery, the lower PET uptake was registered at postoperative imaging, with significant improvement in survival [25].
Despite the results on the usefulness of PET data and their integration in the surgical planning, the introduction of PET imaging in the routine surgical practice has still not been achieved.
Focusing on EOR, different tools, used as single or in combination, have been investigated and promoted in the last decades: fluorophores detected by specific microscope filters [7,89,90,91,92,93,94,95], iMRI [10,11], iUS [12], CE-US [13], fibertracking [96,97], neuronavigation systems [98], and intraoperative neuromonitoring [99].
Each one of these tools, with its own advantages and disadvantages, seeks to increase EOR while preserving neurological functions.
Leaving out the restrictions of a clinical facility to produce radiolabeled amino acids, a possible limitation in the diffusion of PET imaging as an integrated tool in surgical planning could be searched in the intrinsic disadvantage of the neuronavigation system. Despite the widespread diffusion of the latter tool, glioma resection cannot rely exclusively on images. Indeed, neuronavigation is burdened by few limits and errors, such as the brain shift after craniotomy or after dural opening or yet during tumor resection, decreasing the accuracy of space coordinates registered before skin incision [100].
A few authors who have investigated the role of PET imaging in glioma have performed bioptic samples before starting resection, immediately after dural opening in order to keep brain shift at a minimum [31,34,35]. In other cases, a Nelaton catheter was introduced under navigation guidance and anchored to the area that was planned for biopsy [36]. A few others have performed a biopsy before opening the dura [38,40] or before craniotomy [42], and there have been reports of nonlinear registration of intraoperative 3D ultrasound with preoperative FLAIR sequence using a specific algorithm, such as RaPTOR [39].
Live imaging, such as iMRI and/or iUS, can mitigate the problem, but it does not provide the same class of information supplied by PET imaging. Fluorescence-guided surgery can address immediately the neoplastic tissue inside the boundary or even beyond the standard MRI contrast-enhanced borders. Indeed, 5-ALA could aid the surgeon in reaching a supratotal resection, highlighting the glial cells outside the necrotic core of the tumor, while possibly increasing the risk of postoperative neurological deficit [15,101]. Despite this fact, 5-ALA carries a few limitations: in addition to economic issues, patient preparation, and possible side effects, the type of information that 5-ALA provides is different from those offered by radiolabeled amino acids [34,102].
Since the majority of studies have investigated the pathologic “meaning” of the AA-PET-positive tissue obtained with biopsy, only a few have analyzed the impact of performing a resection with the integration of AA-PET imaging: although PET-positive areas are often beyond the border of a contrast-enhanced nodule, no increase in neurological deficit has been reported.
Despite being mentioned in the “only biopsy” group, the multicenter clinical trial by Wakabayashi et al. [43] interestingly reported a modification of the extent of resection considered in the surgical planning of the use of 18-fluciclovine-PET in 47.2% of cases, increasing by 47.8% the resection of high-grade glioma.
Aiming for the resection of AA-PET-positive areas and BTV could be a good compromise between “FLAIRectomy” and classical GTR. However, as the functional result of the patient is the surgeon’s real aim, it is clear that an image-based resection has its well-known limitations [103,104,105].

5. Conclusions

Although an established role was achieved in different fields of glioma management, few data are currently available on PET-guided surgery in high-grade gliomas of the adult. However, with the emergence of the supramaximal resection concept and the lack of reliable radiologic methods to define the microscopic extent of the tumor, a preoperative PET role may assume greater relevance. In combination with other tools, such as MRI, neuronavigation, and fluorophores, great expectations could be reserved in supporting an EOR beyond macroscopically pathologic margins and in tumor border delineation, achieving a more safe and complete resection and an increasingly optimal oncologic–functional balance.
However, beyond the technical aspects pushing in this direction, there is a need for prospective studies evaluating the impact on overall survival and progression-free survival, confirming the validity of PET integration to multimodal neuroimaging in high-grade glioma surgery.

Author Contributions

Conceptualization, R.D.M. and A.B.; methodology, R.D.M. and A.P.; investigation, R.D.M. and A.P.; resources, A.P., A.B. and F.C.; data curation, R.D.M., G.M. and A.M.; writing—original draft preparation, R.D.M.; writing—review and editing, R.D.M., A.B., D.D., M.Z., G.M., P.Z. and F.C.; visualization, R.D.M., A.B. and A.P.; supervision, D.G. and F.C.; project administration, D.G. and F.C. All authors have read and agreed to the published version of the manuscript.

Funding

This research received no external funding.

Conflicts of Interest

The authors declare no conflict of interest.

References

  1. Louis, D.N.; Perry, A.; Wesseling, P.; Brat, D.J.; Cree, I.A.; Figarella-Branger, D.; Hawkins, C.; Ng, H.K.; Pfister, S.M.; Reifenberger, G.; et al. The 2021 WHO classification of tumors of the central nervous system: A summary. Neuro Oncol. 2021, 23, 1231–1251. [Google Scholar] [CrossRef] [PubMed]
  2. Ostrom, Q.T.; Cioffi, G.; Waite, K.; Kruchko, C.; Barnholtz-Sloan, J.S. CBTRUS Statistical Report: Primary Brain and Other Central Nervous System Tumors Diagnosed in the United States in 2014–2018. Neuro Oncol. 2021, 23, iii1–iii105. [Google Scholar] [CrossRef] [PubMed]
  3. Stupp, R.; Hegi, M.E.; Mason, W.P.; van den Bent, M.J.; Taphoorn, M.J.; Janzer, R.C.; Ludwin, S.K.; Allgeier, A.; Fisher, B.; Belanger, K.; et al. Effects of radiotherapy with concomitant and adjuvant temozolomide versus radiotherapy alone on survival in glioblastoma in a randomised phase III study: 5-year analysis of the EORTC-NCIC trial. Lancet Oncol. 2009, 10, 459–466. [Google Scholar] [CrossRef] [PubMed]
  4. Sanai, N.; Berger, M.S. Glioma extent of resection and its impact on patient outcome. Neurosurgery 2008, 62, 753–764. [Google Scholar] [CrossRef] [Green Version]
  5. Sanai, N.; Polley, M.Y.; McDermott, M.W.; Parsa, A.T.; Berger, M.S. An extent of resection threshold for newly diagnosed glioblastomas: Clinical article. J. Neurosurg. 2011, 115, 3–8. [Google Scholar] [CrossRef] [Green Version]
  6. Karschnia, P.; Vogelbaum, M.A.; van den Bent, M.; Cahill, D.P.; Bello, L.; Narita, Y.; Berger, M.S.; Weller, M.; Tonn, J.C. Evidence-based recommendations on categories for extent of resection in diffuse glioma. Eur. J. Cancer 2021, 149, 23–33. [Google Scholar] [CrossRef]
  7. Gandhi, S.; Meybodi, A.T.; Belykh, E.; Cavallo, C.; Zhao, X.; Pasha Syed, M.; Borba Moreira, L.; Lawton, M.T.; Nakaji, P.; Preul, M.C. Survival Outcomes Among Patients With High-Grade Glioma Treated With 5-Aminolevulinic Acid-Guided Surgery: A Systematic Review and Meta-Analysis. Front. Oncol. 2019, 9, 620. [Google Scholar] [CrossRef] [Green Version]
  8. Smith, E.J.; Gohil, K.; Thompson, C.M.; Naik, A.; Hassaneen, W. Fluorescein-Guided Resection of High Grade Gliomas: A Meta-Analysis. World Neurosurg. 2021, 155, 181–188.e7. [Google Scholar] [CrossRef]
  9. Willems, P.W.A.; Taphoorn, M.J.B.; Burger, H.; Van Der Sprenkel, J.W.B.; Tulleken, C.A.F. Effectiveness of neuronavigation in resecting solitary intracerebral contrast-enhancing tumors: A randomized controlled trial. J. Neurosurg. 2006, 104, 360–368. [Google Scholar] [CrossRef] [Green Version]
  10. Hatiboglu, M.A.; Weinberg, J.S.; Suki, D.; Rao, G.; Prabhu, S.S.; Shah, K.; Jackson, E.; Sawaya, R. Impact of intraoperative high-field magnetic resonance imaging guidance on glioma surgery: A prospective volumetric analysis. Neurosurgery 2009, 64, 1073–1081. [Google Scholar] [CrossRef]
  11. Senft, C.; Bink, A.; Franz, K.; Vatter, H.; Gasser, T.; Seifert, V. Intraoperative MRI guidance and extent of resection in glioma surgery: A randomised, controlled trial. Lancet. Oncol. 2011, 12, 997–1003. [Google Scholar] [CrossRef] [PubMed]
  12. Moiyadi, A.V.; Shetty, P.M.; Mahajan, A.; Udare, A.; Sridhar, E. Usefulness of three-dimensional navigable intraoperative ultrasound in resection of brain tumors with a special emphasis on malignant gliomas. Acta Neurochir. 2013, 155, 2217–2225. [Google Scholar] [CrossRef]
  13. Prada, F.; Del Bene, M.; Fornaro, R.; Vetrano, I.G.; Martegani, A.; Aiani, L.; Sconfienza, L.M.; Mauri, G.; Solbiati, L.; Pollo, B.; et al. Identification of residual tumor with intraoperative contrast-enhanced ultrasound during glioblastoma resection. Neurosurg. Focus 2016, 40, E7. [Google Scholar] [CrossRef] [Green Version]
  14. Sastry, R.; Bi, W.L.; Pieper, S.; Frisken, S.; Kapur, T.; Wells, W.; Golby, A.J. Applications of Ultrasound in the Resection of Brain Tumors. J. Neuroimaging 2017, 27, 5–15. [Google Scholar] [CrossRef] [Green Version]
  15. Li, Y.M.; Suki, D.; Hess, K.; Sawaya, R. The influence of maximum safe resection of glioblastoma on survival in 1229 patients: Can we do better than gross-total resection? J. Neurosurg. 2016, 124, 977–988. [Google Scholar] [CrossRef] [Green Version]
  16. Pessina, F.; Navarria, P.; Cozzi, L.; Ascolese, A.M.; Simonelli, M.; Santoro, A.; Clerici, E.; Rossi, M.; Scorsetti, M.; Bello, L. Maximize surgical resection beyond contrast-enhancing boundaries in newly diagnosed glioblastoma multiforme: Is it useful and safe? A single institution retrospective experience. J. Neurooncol. 2017, 135, 129–139. [Google Scholar] [CrossRef] [PubMed]
  17. Esquenazi, Y.; Friedman, E.; Liu, Z.; Zhu, J.J.; Hsu, S.; Tandon, N. The Survival Advantage of “supratotal” Resection of Glioblastoma Using Selective Cortical Mapping and the Subpial Technique. Neurosurgery 2017, 81, 275–288. [Google Scholar] [CrossRef] [PubMed]
  18. Certo, F.; Altieri, R.; Maione, M.; Schonauer, C.; Sortino, G.; Fiumanò, G.; Tirrò, E.; Massimino, M.; Broggi, G.; Vigneri, P.; et al. FLAIRectomy in Supramarginal Resection of Glioblastoma Correlates With Clinical Outcome and Survival Analysis: A Prospective, Single Institution, Case Series. Oper. Neurosurg. 2021, 20, 151–163. [Google Scholar] [CrossRef] [PubMed]
  19. Seker-Polat, F.; Degirmenci, N.P.; Solaroglu, I.; Bagci-Onder, T. Tumor Cell Infiltration into the Brain in Glioblastoma: From Mechanisms to Clinical Perspectives. Cancers 2022, 14, 443. [Google Scholar] [CrossRef]
  20. Bianconi, A.; Aruta, G.; Rizzo, F.; Salvati, L.F.; Zeppa, P.; Garbossa, D.; Cofano, F. Systematic Review on Tumor Microenvironment in Glial Neoplasm: From Understanding Pathogenesis to Future Therapeutic Perspectives. Int. J. Mol. Sci. 2022, 23, 4166. [Google Scholar] [CrossRef]
  21. Burger, P.C.; Dubois, P.J.; Schold, S.C.; Smith, K.R.; Odom, G.L.; Crafts, D.C.; Giangaspero, F. Computerized tomographic and pathologic studies of the untreated, quiescent, and recurrent glioblastoma multiforme. J. Neurosurg. 1983, 58, 159–169. [Google Scholar] [CrossRef]
  22. De Bonis, P.; Anile, C.; Pompucci, A.; Fiorentino, A.; Balducci, M.; Chiesa, S.; Lauriola, L.; Maira, G.; Mangiola, A. The influence of surgery on recurrence pattern of glioblastoma. Clin. Neurol. Neurosurg. 2013, 115, 37–43. [Google Scholar] [CrossRef] [PubMed]
  23. Altieri, R.; Barbagallo, D.; Certo, F.; Broggi, G.; Ragusa, M.; Di Pietro, C.; Caltabiano, R.; Magro, G.; Peschillo, S.; Purrello, M.; et al. Peritumoral Microenvironment in High-Grade Gliomas: From FLAIRectomy to Microglia-Glioma Cross-Talk. Brain Sci. 2021, 11, 200. [Google Scholar] [CrossRef] [PubMed]
  24. Lohmann, P.; Stavrinou, P.; Lipke, K.; Bauer, E.K.; Ceccon, G.; Werner, J.M.; Neumaier, B.; Fink, G.R.; Shah, N.J.; Langen, K.J.; et al. FET PET reveals considerable spatial differences in tumour burden compared to conventional MRI in newly diagnosed glioblastoma. Eur. J. Nucl. Med. Mol. Imaging 2019, 46, 591–602. [Google Scholar] [CrossRef] [PubMed] [Green Version]
  25. Müther, M.; Koch, R.; Weckesser, M.; Sporns, P.; Schwindt, W.; Stummer, W. 5-Aminolevulinic Acid Fluorescence-Guided Resection of 18F-FET-PET Positive Tumor Beyond Gadolinium Enhancing Tumor Improves Survival in Glioblastoma. Neurosurgery 2019, 85, E1020–E1029. [Google Scholar] [CrossRef] [Green Version]
  26. Albert, N.L.; Weller, M.; Suchorska, B.; Galldiks, N.; Soffietti, R.; Kim, M.M.; La Fougère, C.; Pope, W.; Law, I.; Arbizu, J.; et al. Response Assessment in Neuro-Oncology working group and European Association for Neuro-Oncology recommendations for the clinical use of PET imaging in gliomas. Neuro Oncol. 2016, 18, 1199–1208. [Google Scholar] [CrossRef]
  27. Law, I.; Albert, N.L.; Arbizu, J.; Boellaard, R.; Drzezga, A.; Galldiks, N.; la Fougère, C.; Langen, K.J.; Lopci, E.; Lowe, V.; et al. Joint EANM/EANO/RANO practice guidelines/SNMMI procedure standards for imaging of gliomas using PET with radiolabelled amino acids and [18 F]FDG: Version 1.0. Eur. J. Nucl. Med. Mol. Imaging 2019, 46, 540–557. [Google Scholar] [CrossRef] [Green Version]
  28. Inoue, A.; Ohnishi, T.; Kohno, S.; Ohue, S.; Nishikawa, M.; Suehiro, S.; Matsumoto, S.; Ozaki, S.; Fukushima, M.; Kurata, M.; et al. Met-PET uptake index for total tumor resection: Identification of 11 C-methionine uptake index as a goal for total tumor resection including infiltrating tumor cells in glioblastoma. Neurosurg. Rev. 2021, 44, 587–597. [Google Scholar] [CrossRef]
  29. Pirotte, B.; Goldman, S.; Massager, N.; David, P.; Wikler, D.; Lipszyc, M.; Salmon, I.; Brotchi, J.; Levivier, M. Combined use of 18F-fluorodeoxyglucose and 11C-methionine in 45 positron emission tomography-guided stereotactic brain biopsies. J. Neurosurg. 2004, 101, 476–483. [Google Scholar] [CrossRef]
  30. Stockhammer, F.; Thomale, U.W.; Plotkin, M.; Hartmann, C.; Von Deimling, A. Association between fluorine-18–labeled fluorodeoxyglucose uptake and 1p and 19q loss of heterozygosity in World Health Organization Grade II gliomas. J. Neurosurg. 2007, 106, 633–637. [Google Scholar] [CrossRef]
  31. Stockhammer, F.; Plotkin, M.; Amthauer, H.; Landeghem, F.K.H.; Woiciechowsky, C. Correlation of F-18-fluoro-ethyl-tyrosin uptake with vascular and cell density in non-contrast-enhancing gliomas. J. Neurooncol. 2008, 88, 205–210. [Google Scholar] [CrossRef]
  32. Weber, M.A.; Henze, M.; Tüttenberg, J.; Stieltjes, B.; Meissner, M.; Zimmer, F.; Burkholder, I.; Kroll, A.; Combs, S.E.; Vogt-Schaden, M.; et al. Biopsy targeting gliomas: Do functional imaging techniques identify similar target areas? Investig. Radiol. 2010, 45, 755–768. [Google Scholar] [CrossRef]
  33. Kunz, M.; Thon, N.; Eigenbrod, S.; Hartmann, C.; Egensperger, R.; Herms, J.; Geisler, J.; La Fougere, C.; Lutz, J.; Linn, J.; et al. Hot spots in dynamic (18)FET-PET delineate malignant tumor parts within suspected WHO grade II gliomas. Neuro Oncol. 2011, 13, 307–316. [Google Scholar] [CrossRef] [PubMed]
  34. Floeth, F.W.; Sabel, M.; Ewelt, C.; Stummer, W.; Felsberg, J.; Reifenberger, G.; Steiger, H.J.; Stoffels, G.; Coenen, H.H.; Langen, K.J. Comparison of 18F-FET PET and 5-ALA fluorescence in cerebral gliomas. Eur. J. Nucl. Med. Mol. Imaging 2011, 38, 731–741. [Google Scholar] [CrossRef]
  35. Ewelt, C.; Floeth, F.W.; Felsberg, J.; Steiger, H.J.; Sabel, M.; Langen, K.J.; Stoffels, G.; Stummer, W. Finding the anaplastic focus in diffuse gliomas: The value of Gd-DTPA enhanced MRI, FET-PET, and intraoperative, ALA-derived tissue fluorescence. Clin. Neurol. Neurosurg. 2011, 113, 541–547. [Google Scholar] [CrossRef] [PubMed]
  36. Arita, H.; Kinoshita, M.; Kagawa, N.; Fujimoto, Y.; Kishima, H.; Hashimoto, N.; Yoshimine, T. 11C-methionine uptake and intraoperative 5-aminolevulinic acid-induced fluorescence as separate index markers of cell density in glioma: A stereotactic image-histological analysis. Cancer 2012, 118, 1619–1627. [Google Scholar] [CrossRef] [PubMed]
  37. Pafundi, D.H.; Laack, N.N.; Youland, R.S.; Parney, I.F.; Lowe, V.J.; Giannini, C.; Kemp, B.J.; Grams, M.P.; Morris, J.M.; Hoover, J.M.; et al. Biopsy validation of 18F-DOPA PET and biodistribution in gliomas for neurosurgical planning and radiotherapy target delineation: Results of a prospective pilot study. Neuro Oncol. 2013, 15, 1058–1067. [Google Scholar] [CrossRef]
  38. Beppu, T.; Sasaki, T.; Terasaki, K.; Saura, H.; Mtsuura, H.; Ogasawara, K.; Sasaki, M.; Ehara, S.; Iwata, R.; Takai, Y. High-uptake areas on positron emission tomography with the hypoxic radiotracer 18F-FRP170 in glioblastomas include regions retaining proliferative activity under hypoxia. Ann. Nucl. Med. 2015, 29, 336. [Google Scholar] [CrossRef] [Green Version]
  39. Karlberg, A.; Berntsen, E.M.; Johansen, H.; Skjulsvik, A.J.; Reinertsen, I.; Dai, H.Y.; Xiao, Y.; Rivaz, H.; Borghammer, P.; Solheim, O.; et al. 18F-FACBC PET/MRI in Diagnostic Assessment and Neurosurgery of Gliomas. Clin. Nucl. Med. 2019, 44, 550–559. [Google Scholar] [CrossRef] [Green Version]
  40. Fernandez, P.; Zanotti-Fregonara, P.; Eimer, S.; Gimbert, E.; Monteil, P.; Penchet, G.; Lamare, F.; Perez, P.; Vimont, D.; Ledure, S.; et al. Combining 3′-Deoxy-3′-[18F] fluorothymidine and MRI increases the sensitivity of glioma volume detection. Nucl. Med. Commun. 2019, 40, 1066–1071. [Google Scholar] [CrossRef]
  41. Ponisio, M.R.; McConathy, J.E.; Dahiya, S.M.; Miller-Thomas, M.M.; Rich, K.M.; Salter, A.; Wang, Q.; LaMontagne, P.J.; Guzmán Pérez-Carrillo, G.J.; Benzinger, T.L.S. Dynamic 18 F-FDOPA-PET/MRI for the preoperative evaluation of gliomas: Correlation with stereotactic histopathology. Neuro -Oncol. Pract. 2020, 7, 656–667. [Google Scholar] [CrossRef] [PubMed]
  42. Verburg, N.; Koopman, T.; Yaqub, M.M.; Hoekstra, O.S.; Lammertsma, A.A.; Barkhof, F.; Pouwels, P.J.W.; Reijneveld, J.C.; Heimans, J.J.; Rozemuller, A.J.M.; et al. Improved detection of diffuse glioma infiltration with imaging combinations: A diagnostic accuracy study. Neuro Oncol. 2020, 22, 412. [Google Scholar] [CrossRef] [PubMed]
  43. Wakabayashi, T.; Hirose, Y.; Miyake, K.; Arakawa, Y.; Kagawa, N.; Nariai, T.; Narita, Y.; Nishikawa, R.; Tsuyuguchi, N.; Fukami, T.; et al. Determining the extent of tumor resection at surgical planning with 18F-fluciclovine PET/CT in patients with suspected glioma: Multicenter phase III trials. Ann. Nucl. Med. 2021, 35, 1279–1292. [Google Scholar] [CrossRef] [PubMed]
  44. Pauleit, D.; Floeth, F.; Hamacher, K.; Riemenschneider, M.J.; Reifenberger, G.; Müller, H.W.; Zilles, K.; Coenen, H.H.; Langen, K.J. O-(2-[18F]fluoroethyl)-L-tyrosine PET combined with MRI improves the diagnostic assessment of cerebral gliomas. Brain 2005, 128, 678–687. [Google Scholar] [CrossRef] [PubMed] [Green Version]
  45. Pirotte, B.J.M.; Levivier, M.; Goldman, S.; Massager, N.; Wikler, D.; Dewitte, O.; Bruneau, M.; Rorive, S.; David, P.; Brotchi, J. Positron emission tomography-guided volumetric resection of supratentorial high-grade gliomas: A survival analysis in 66 consecutive patients. Neurosurgery 2009, 64, 471–481. [Google Scholar] [CrossRef]
  46. Ort, J.; Hamou, H.A.; Kernbach, J.M.; Hakvoort, K.; Blume, C.; Lohmann, P.; Galldiks, N.; Heiland, D.H.; Mottaghy, F.M.; Clusmann, H.; et al. 18 F-FET-PET-guided gross total resection improves overall survival in patients with WHO grade III/IV glioma: Moving towards a multimodal imaging-guided resection. J. Neurooncol. 2021, 155, 71–80. [Google Scholar] [CrossRef]
  47. Kracht, L.W.; Miletic, H.; Busch, S.; Jacobs, A.H.; Voges, J.; Hoevels, M.; Klein, J.C.; Herholz, K.; Heiss, W.D. Delineation of brain tumor extent with [11C]L-methionine positron emission tomography: Local comparison with stereotactic histopathology. Clin. Cancer Res. 2004, 10, 7163–7170. [Google Scholar] [CrossRef] [Green Version]
  48. Torii, K.; Tsuyuguchi, N.; Kawabe, J.; Sunada, I.; Hara, M.; Shiomi, S. Correlation of amino-acid uptake using methionine PET and histological classifications in various gliomas. Ann. Nucl. Med. 2005, 19, 677–683. [Google Scholar] [CrossRef]
  49. Nojiri, T.; Nariai, T.; Aoyagi, M.; Senda, M.; Ishii, K.; Ishiwata, K.; Ohno, K. Contributions of biological tumor parameters to the incorporation rate of L: -[methyl-(11)C] methionine into astrocytomas and oligodendrogliomas. J. Neurooncol. 2009, 93, 233–241. [Google Scholar] [CrossRef] [Green Version]
  50. Okita, Y.; Kinoshita, M.; Goto, T.; Kagawa, N.; Kishima, H.; Shimosegawa, E.; Hatazawa, J.; Hashimoto, N.; Yoshimine, T. (11)C-methionine uptake correlates with tumor cell density rather than with microvessel density in glioma: A stereotactic image-histology comparison. Neuroimage 2010, 49, 2977–2982. [Google Scholar] [CrossRef]
  51. Roberts, D.W.; Valdés, P.A.; Harris, B.T.; Fontaine, K.M.; Hartov, A.; Fan, X.; Ji, S.; Lollis, S.S.; Pogue, B.W.; Leblond, F.; et al. Coregistered fluorescence-enhanced tumor resection of malignant glioma: Relationships between δ-aminolevulinic acid-induced protoporphyrin IX fluorescence, magnetic resonance imaging enhancement, and neuropathological parameters. Clinical article. J. Neurosurg. 2011, 114, 595–603. [Google Scholar] [CrossRef] [PubMed] [Green Version]
  52. Dunet, V.; Pomoni, A.; Hottinger, A.; Nicod-Lalonde, M.; Prior, J.O. Performance of 18F-FET versus 18F-FDG-PET for the diagnosis and grading of brain tumors: Systematic review and meta-analysis. Neuro Oncol. 2015, 18, 426–434. [Google Scholar] [CrossRef] [PubMed] [Green Version]
  53. Heiss, P.; Mayer, S.; Herz, M.; Wester, H.-J.; Schwaiger, M.; Senekowitsch-Schmidtke, R. Investigation of Transport Mechanism and Uptake Kinetics of O-(2-[18F]Fluoroethyl)-L-Tyrosine In Vitro and In Vivo. J. Nucl. Med. 1999, 40, 1367–1373. [Google Scholar] [PubMed]
  54. Okubo, S.; Zhen, H.N.; Kawai, N.; Nishiyama, Y.; Haba, R.; Tamiya, T. Correlation of L-methyl-11C-methionine (MET) uptake with L-type amino acid transporter 1 in human gliomas. J. Neurooncol. 2010, 99, 217–225. [Google Scholar] [CrossRef]
  55. Youland, R.S.; Kitange, G.J.; Peterson, T.E.; Pafundi, D.H.; Ramiscal, J.A.; Pokorny, J.L.; Giannini, C.; Laack, N.N.; Parney, I.F.; Lowe, V.J.; et al. The role of LAT1 in (18)F-DOPA uptake in malignant gliomas. J. Neurooncol. 2013, 111, 11–18. [Google Scholar] [CrossRef]
  56. Juhász, C.; Dwivedi, S.; Kamson, D.O.; Michelhaugh, S.K.; Mittal, S. Comparison of amino acid positron emission tomographic radiotracers for molecular imaging of primary and metastatic brain tumors. Mol. Imaging 2014, 13, 7290.2014.00015. [Google Scholar] [CrossRef]
  57. Morana, G.; Piccardo, A.; Milanaccio, C.; Puntoni, M.; Nozza, P.; Cama, A.; Zefiro, D.; Cabria, M.; Rossi, A.; Garrè, M.L. Value of 18F-3,4-dihydroxyphenylalanine PET/MR image fusion in pediatric supratentorial infiltrative astrocytomas: A prospective pilot study. J. Nucl. Med. 2014, 55, 718–723. [Google Scholar] [CrossRef] [Green Version]
  58. Bell, C.; Dowson, N.; Puttick, S.; Gal, Y.; Thomas, P.; Fay, M.; Smith, J.; Rose, S. Increasing feasibility and utility of (18)F-FDOPA PET for the management of glioma. Nucl. Med. Biol. 2015, 42, 788–795. [Google Scholar] [CrossRef] [Green Version]
  59. Morana, G.; Piccardo, A.; Tortora, D.; Puntoni, M.; Severino, M.; Nozza, P.; Ravegnani, M.; Consales, A.; Mascelli, S.; Raso, A.; et al. Grading and outcome prediction of pediatric diffuse astrocytic tumors with diffusion and arterial spin labeling perfusion MRI in comparison with 18F-DOPA PET. Eur. J. Nucl. Med. Mol. Imaging 2017, 44, 2084–2093. [Google Scholar] [CrossRef]
  60. Zaragori, T.; Ginet, M.; Marie, P.Y.; Roch, V.; Grignon, R.; Gauchotte, G.; Rech, F.; Blonski, M.; Lamiral, Z.; Taillandier, L.; et al. Use of static and dynamic [18 F]-F-DOPA PET parameters for detecting patients with glioma recurrence or progression. EJNMMI Res. 2020, 10, 56. [Google Scholar] [CrossRef]
  61. Somme, F.; Bender, L.; Namer, I.J.; Noël, G.; Bund, C. Usefulness of 18 F-FDOPA PET for the management of primary brain tumors: A systematic review of the literature. Cancer Imaging 2020, 20, 70. [Google Scholar] [CrossRef]
  62. Sipos, D.; László, Z.; Tóth, Z.; Kovács, P.; Tollár, J.; Gulybán, A.; Lakosi, F.; Repa, I.; Kovács, A. Additional Value of 18F-FDOPA Amino Acid Analog Radiotracer to Irradiation Planning Process of Patients With Glioblastoma Multiforme. Front. Oncol. 2021, 11, 699360. [Google Scholar] [CrossRef] [PubMed]
  63. Girard, A.; Le Reste, P.J.; Metais, A.; Chaboub, N.; Devillers, A.; Saint-Jalmes, H.; Le Jeune, F.; Palard-Novello, X. Additive Value of Dynamic FDOPA PET/CT for Glioma Grading. Front. Med. 2021, 8, 705996. [Google Scholar] [CrossRef] [PubMed]
  64. Grosu, A.L.; Astner, S.T.; Riedel, E.; Nieder, C.; Wiedenmann, N.; Heinemann, F.; Schwaiger, M.; Molls, M.; Wester, H.J.; Weber, W.A. An interindividual comparison of O-(2-[18F]fluoroethyl)-L-tyrosine (FET)- and L-[methyl-11C]methionine (MET)-PET in patients with brain gliomas and metastases. Int. J. Radiat. Oncol. Biol. Phys. 2011, 81, 1049–1058. [Google Scholar] [CrossRef] [PubMed]
  65. Weber, W.A.; Wester, H.J.; Grosu, A.L.; Herz, M.; Dzewas, B.; Feldmann, H.J.; Molls, M.; Stöcklin, G.; Schwaiger, M. O-(2-[18F]fluoroethyl)-L-tyrosine and L-[methyl-11C]methionine uptake in brain tumours: Initial results of a comparative study. Eur. J. Nucl. Med. 2000, 27, 542–549. [Google Scholar] [CrossRef] [PubMed]
  66. Becherer, A.; Karanikas, G.; Szabó, M.; Zettinig, G.; Asenbaum, S.; Marosi, C.; Henk, C.; Wunderbaldinger, P.; Czech, T.; Wadsak, W.; et al. Brain tumour imaging with PET: A comparison between [18F]fluorodopa and [11C]methionine. Eur. J. Nucl. Med. Mol. Imaging 2003, 30, 1561–1567. [Google Scholar] [CrossRef] [PubMed]
  67. Singhal, T.; Narayanan, T.K.; Jain, V.; Mukherjee, J.; Mantil, J. 11C-L-methionine positron emission tomography in the clinical management of cerebral gliomas. Mol. Imaging Biol. 2008, 10, 1–18. [Google Scholar] [CrossRef]
  68. Pöpperl, G.; Kreth, F.W.; Mehrkens, J.H.; Herms, J.; Seelos, K.; Koch, W.; Gildehaus, F.J.; Kretzschmar, H.A.; Tonn, J.C.; Tatsch, K. FET PET for the evaluation of untreated gliomas: Correlation of FET uptake and uptake kinetics with tumour grading. Eur. J. Nucl. Med. Mol. Imaging 2007, 34, 1933–1942. [Google Scholar] [CrossRef]
  69. Xiao, J.; Jin, Y.; Nie, J.; Chen, F.; Ma, X. Diagnostic and grading accuracy of 18 F-FDOPA PET and PET/CT in patients with gliomas: A systematic review and meta-analysis. BMC Cancer 2019, 19, 767. [Google Scholar] [CrossRef] [Green Version]
  70. Verger, A.; Stoffels, G.; Bauer, E.K.; Lohmann, P.; Blau, T.; Fink, G.R.; Neumaier, B.; Shah, N.J.; Langen, K.J.; Galldiks, N. Static and dynamic 18 F-FET PET for the characterization of gliomas defined by IDH and 1p/19q status. Eur. J. Nucl. Med. Mol. Imaging 2018, 45, 443–451. [Google Scholar] [CrossRef]
  71. Katsanos, A.H.; Alexiou, G.A.; Fotopoulos, A.D.; Jabbour, P.; Kyritsis, A.P.; Sioka, C. Performance of 18F-FDG, 11C-Methionine, and 18F-FET PET for Glioma Grading: A Meta-analysis. Clin. Nucl. Med. 2019, 44, 864–869. [Google Scholar] [CrossRef] [PubMed]
  72. Tovi, M.; Hartman, M.; Lilja, A.; Ericsson, A. MR imaging in cerebral gliomas: Tissue component analysis in correlation with histopathology of whole-brain specimens. Acta Radiol. 1994, 35, 495–505. [Google Scholar] [CrossRef]
  73. Ginsberg, L.E.; Fuller, G.N.; Hashmi, M.; Leeds, N.E.; Schomer, D.F. The significance of lack of MR contrast enhancement of supratentorial brain tumors in adults: Histopathological evaluation of a series. Surg. Neurol. 1998, 49, 436–440. [Google Scholar] [CrossRef] [PubMed]
  74. Eidel, O.; Burth, S.; Neumann, J.O.; Kieslich, P.J.; Sahm, F.; Jungk, C.; Kickingereder, P.; Bickelhaupt, S.; Mundiyanapurath, S.; Bäumer, P.; et al. Tumor Infiltration in Enhancing and Non-Enhancing Parts of Glioblastoma: A Correlation with Histopathology. PLoS ONE 2017, 12, e0169292. [Google Scholar] [CrossRef] [Green Version]
  75. Kinoshita, M.; Arita, H.; Okita, Y.; Kagawa, N.; Kishima, H.; Hashimoto, N.; Tanaka, H.; Watanabe, Y.; Shimosegawa, E.; Hatazawa, J.; et al. Comparison of diffusion tensor imaging and 11 C-methionine positron emission tomography for reliable prediction of tumor cell density in gliomas. J. Neurosurg. 2016, 125, 1136–1142. [Google Scholar] [CrossRef] [PubMed] [Green Version]
  76. Yang, Y.; He, M.Z.; Li, T.; Yang, X. MRI combined with PET-CT of different tracers to improve the accuracy of glioma diagnosis: A systematic review and meta-analysis. Neurosurg. Rev. 2019, 42, 185–195. [Google Scholar] [CrossRef] [Green Version]
  77. Zhang-Yin, J.T.; Girard, A.; Bertaux, M. What Does PET Imaging Bring to Neuro-Oncology in 2022? A Review. Cancers 2022, 14, 879. [Google Scholar] [CrossRef]
  78. Kinoshita, M.; Goto, T.; Arita, H.; Okita, Y.; Isohashi, K.; Kagawa, N.; Fujimoto, Y.; Kishima, H.; Shimosegawa, E.; Saitoh, Y.; et al. Imaging 18F-fluorodeoxy glucose/ 11C-methionine uptake decoupling for identification of tumor cell infiltration in peritumoral brain edema. J. Neurooncol. 2012, 106, 417–425. [Google Scholar] [CrossRef]
  79. Kinoshita, M.; Arita, H.; Goto, T.; Okita, Y.; Isohashi, K.; Watabe, T.; Kagawa, N.; Fujimoto, Y.; Kishima, H.; Shimosegawa, E.; et al. A novel PET index, 18F-FDG-11C-methionine uptake decoupling score, reflects glioma cell infiltration. J. Nucl. Med. 2012, 53, 1701–1708. [Google Scholar] [CrossRef] [PubMed] [Green Version]
  80. Kinoshita, M.; Uchikoshi, M.; Tateishi, S.; Miyazaki, S.; Sakai, M.; Ozaki, T.; Asai, K.; Fujita, Y.; Matsuhashi, T.; Kanemura, Y.; et al. Magnetic Resonance Relaxometry for Tumor Cell Density Imaging for Glioma: An Exploratory Study via 11 C-Methionine PET and Its Validation via Stereotactic Tissue Sampling. Cancers 2021, 13, 4067. [Google Scholar] [CrossRef]
  81. Grosu, A.L.; Weber, W.A.; Riedel, E.; Jeremic, B.; Nieder, C.; Franz, M.; Gumprecht, H.; Jaeger, R.; Schwaiger, M.; Molls, M. L-(methyl-11C) methionine positron emission tomography for target delineation in resected high-grade gliomas before radiotherapy. Int. J. Radiat. Oncol. Biol. Phys. 2005, 63, 64–74. [Google Scholar] [CrossRef] [PubMed]
  82. Matsuo, M.; Miwa, K.; Tanaka, O.; Shinoda, J.; Nishibori, H.; Tsuge, Y.; Yano, H.; Iwama, T.; Hayashi, S.; Hoshi, H.; et al. Impact of [11C]methionine positron emission tomography for target definition of glioblastoma multiforme in radiation therapy planning. Int. J. Radiat. Oncol. Biol. Phys. 2012, 82, 83–89. [Google Scholar] [CrossRef] [PubMed]
  83. Pirotte, B.; Goldman, S.; Dewitte, O.; Massager, N.; Wikler, D.; Lefranc, F.; Taib, N.O.B.; Rorive, S.; David, P.; Brotchi, J.; et al. Integrated positron emission tomography and magnetic resonance imaging-guided resection of brain tumors: A report of 103 consecutive procedures. J. Neurosurg. 2006, 104, 238–253. [Google Scholar] [CrossRef]
  84. Dunet, V.; Rossier, C.; Buck, A.; Stupp, R.; Prior, J.O. Performance of 18F-fluoro-ethyl-tyrosine (18F-FET) PET for the differential diagnosis of primary brain tumor: A systematic review and Metaanalysis. J. Nucl. Med. 2012, 53, 207–214. [Google Scholar] [CrossRef] [PubMed] [Green Version]
  85. Lapa, C.; Linsenmann, T.; Monoranu, C.M.; Samnick, S.; Buck, A.K.; Bluemel, C.; Czernin, J.; Kessler, A.F.; Homola, G.A.; Ernestus, R.I.; et al. Comparison of the amino acid tracers 18F-FET and 18F-DOPA in high-grade glioma patients. J. Nucl. Med. 2014, 55, 1611–1616. [Google Scholar] [CrossRef] [PubMed] [Green Version]
  86. Kratochwil, C.; Combs, S.E.; Leotta, K.; Afshar-Oromieh, A.; Rieken, S.; Debus, J.; Haberkorn, U.; Giesel, F.L. Intra-individual comparison of 18F-FET and 18F-DOPA in PET imaging of recurrent brain tumors. Neuro Oncol. 2014, 16, 434. [Google Scholar] [CrossRef] [Green Version]
  87. Morana, G.; Puntoni, M.; Garrè, M.L.; Massollo, M.; Lopci, E.; Naseri, M.; Severino, M.; Tortora, D.; Rossi, A.; Piccardo, A. Ability of (18)F-DOPA PET/CT and fused (18)F-DOPA PET/MRI to assess striatal involvement in paediatric glioma. Eur. J. Nucl. Med. Mol. Imaging 2016, 43, 1664–1672. [Google Scholar] [CrossRef]
  88. Stockhammer, F.; Misch, M.; Horn, P.; Koch, A.; Fonyuy, N.; Plotkin, M. Association of F18-fluoro-ethyl-tyrosin uptake and 5-aminolevulinic acid-induced fluorescence in gliomas. Acta Neurochir. 2009, 151, 1377–1383. [Google Scholar] [CrossRef]
  89. Díez Valle, R.; Tejada Solis, S.; Idoate Gastearena, M.A.; García De Eulate, R.; Domínguez Echávarri, P.; Aristu Mendiroz, J. Surgery guided by 5-aminolevulinic fluorescence in glioblastoma: Volumetric analysis of extent of resection in single-center experience. J. Neurooncol. 2011, 102, 105–113. [Google Scholar] [CrossRef]
  90. Jenkinson, M.D.; Barone, D.G.; Bryant, A.; Vale, L.; Bulbeck, H.; Lawrie, T.A.; Hart, M.G.; Watts, C. Intraoperative imaging technology to maximise extent of resection for glioma. Cochrane Database Syst. Rev. 2018, 2018, CD013630. [Google Scholar] [CrossRef]
  91. Hansen, R.W.; Pedersen, C.B.; Halle, B.; Korshoej, A.R.; Schulz, M.K.; Kristensen, B.W.; Poulsen, F.R. Comparison of 5-aminolevulinic acid and sodium fluorescein for intraoperative tumor visualization in patients with high-grade gliomas: A single-center retrospective study. J. Neurosurg. 2019, 133, 1324–1331. [Google Scholar] [CrossRef] [PubMed]
  92. Della Puppa, A.; Munari, M.; Gardiman, M.P.; Volpin, F. Combined Fluorescence Using 5-Aminolevulinic Acid and Fluorescein Sodium at Glioblastoma Border: Intraoperative Findings and Histopathologic Data About 3 Newly Diagnosed Consecutive Cases. World Neurosurg. 2019, 122, e856–e863. [Google Scholar] [CrossRef] [PubMed]
  93. Specchia, F.M.C.; Monticelli, M.; Zeppa, P.; Bianconi, A.; Zenga, F.; Altieri, R.; Pugliese, B.; Di Perna, G.; Cofano, F.; Tartara, F.; et al. Let Me See: Correlation between 5-ALA Fluorescence and Molecular Pathways in Glioblastoma: A Single Center Experience. Brain Sci. 2021, 11, 795. [Google Scholar] [CrossRef]
  94. Palmieri, G.; Cofano, F.; Salvati, L.F.; Monticelli, M.; Zeppa, P.; Perna, G.D.; Melcarne, A.; Altieri, R.; La Rocca, G.; Sabatino, G.; et al. Fluorescence-Guided Surgery for High-Grade Gliomas: State of the Art and New Perspectives. Technol. Cancer Res. Treat. 2021, 20, 15330338211021605. [Google Scholar] [CrossRef]
  95. Zeppa, P.; De Marco, R.; Monticelli, M.; Massara, A.; Bianconi, A.; Di Perna, G.; Greco Crasto, S.; Cofano, F.; Melcarne, A.; Lanotte, M.M.; et al. Fluorescence-Guided Surgery in Glioblastoma: 5-ALA, SF or Both? Differences between Fluorescent Dyes in 99 Consecutive Cases. Brain Sci 2022, 12, 555. [Google Scholar] [CrossRef]
  96. Tuncer, M.S.; Salvati, L.F.; Grittner, U.; Hardt, J.; Schilling, R.; Bährend, I.; Silva, L.L.; Fekonja, L.S.; Faust, K.; Vajkoczy, P.; et al. Towards a tractography-based risk stratification model for language area associated gliomas. NeuroImage Clin. 2021, 29, 102541. [Google Scholar] [CrossRef] [PubMed]
  97. Salvati, L.F.; De Marco, R.; Palmieri, G.; Minardi, M.; Massara, A.; Pesaresi, A.; Cagetti, B.; Melcarne, A.; Garbossa, D. The Relevant Role of Navigated Tractography in Speech Eloquent Area Glioma Surgery: Single Center Experience. Brain Sci. 2021, 11, 1436. [Google Scholar] [CrossRef] [PubMed]
  98. Zeppa, P.; Neitzert, L.; Mammi, M.; Monticelli, M.; Altieri, R.; Castaldo, M.; Cofano, F.; Borrè, A.; Zenga, F.; Melcarne, A.; et al. How Reliable Are Volumetric Techniques for High-Grade Gliomas? A Comparison Study of Different Available Tools. Neurosurgery 2020, 87, E672–E679. [Google Scholar] [CrossRef]
  99. Altieri, R.; Raimondo, S.; Tiddia, C.; Sammarco, D.; Cofano, F.; Zeppa, P.; Monticelli, M.; Melcarne, A.; Junemann, C.; Zenga, F.; et al. Glioma surgery: From preservation of motor skills to conservation of cognitive functions. J. Clin. Neurosci. 2019, 70, 55–60. [Google Scholar] [CrossRef] [Green Version]
  100. Gerard, I.J.; Kersten-Oertel, M.; Petrecca, K.; Sirhan, D.; Hall, J.A.; Collins, D.L. Brain shift in neuronavigation of brain tumors: A review. Med. Image Anal. 2017, 35, 403–420. [Google Scholar] [CrossRef]
  101. Eyüpoglu, I.Y.; Hore, N.; Merkel, A.; Buslei, R.; Buchfelder, M.; Savaskan, N.; Eyüpoglu, I.Y.; Hore, N.; Merkel, A.; Buslei, R.; et al. Supra-complete surgery via dual intraoperative visualization approach (DiVA) prolongs patient survival in glioblastoma. Oncotarget 2016, 7, 25755–25768. [Google Scholar] [CrossRef] [PubMed]
  102. Pala, A.; Reske, S.N.; Eberhardt, N.; Scheuerle, A.; König, R.; Schmitz, B.; Beer, A.J.; Wirtz, C.R.; Coburger, J. Diagnostic accuracy of intraoperative perfusion-weighted MRI and 5-aminolevulinic acid in relation to contrast-enhanced intraoperative MRI and 11 C-methionine positron emission tomography in resection of glioblastoma: A prospective study. Neurosurg. Rev. 2019, 42, 471–479. [Google Scholar] [CrossRef] [PubMed]
  103. Duffau, H. Is Supratotal Resection of Glioblastoma in Noneloquent Areas Possible? World Neurosurg. 2014, 82, e101–e103. [Google Scholar] [CrossRef] [PubMed]
  104. Duffau, H. Surgery for malignant brain gliomas: Fluorescence-guided resection or functional-based resection? Front. Surg. 2019, 6, 21. [Google Scholar] [CrossRef] [PubMed] [Green Version]
  105. Zigiotto, L.; Annicchiarico, L.; Corsini, F.; Vitali, L.; Falchi, R.; Dalpiaz, C.; Rozzanigo, U.; Barbareschi, M.; Avesani, P.; Papagno, C.; et al. Effects of supra-total resection in neurocognitive and oncological outcome of high-grade gliomas comparing asleep and awake surgery. J. Neurooncol. 2020, 148, 97–108. [Google Scholar] [CrossRef] [PubMed]
Cancers 15 00090 g001 550
Figure 1. PRISMA 2020 flow diagram illustrating the study selection.
Figure 1. PRISMA 2020 flow diagram illustrating the study selection.
Cancers 15 00090 g001
Table
Table 1. List of references where PET imaging was integrated in the neuronavigation system and high-uptake areas were preferentially selected for biopsy.
Table 1. List of references where PET imaging was integrated in the neuronavigation system and high-uptake areas were preferentially selected for biopsy.
Authors, YearNo. of PtsNo. of RecurrenceStudy TypePET RadiotracerPET UseGlioma Grade
(WHO 2021)
Pirotte et al., 2004 [29]320RetrospectiveBoth 18F-FDG and MetComparison of distribution, extent, and relative contributions of 18F-FDG and Met2–4
Pauleit et al., 2005 [44]280ProspectiveFETFET-PET combined with MRI imaging to improve distinction between cellular glioma tissue and unspecific peritumoral brain tissue1–4
Stockhammer et al., 2007 [30]254RetrospectiveFDGPrediction of LOH 1p/19q in grade II gliomas2, 3
Stockhammer et al., 2008 * [31]229ProspectiveFETHistological evaluation of surgically collected tissue in FET-PET-positive areas of non-contrast-enhancing lesions2, 3
Weber et al., 2010 [32]61 10RetrospectiveFLT and FDGMultiparametric evaluation and functional imaging comparison2–4
Kunz et al.,
2010 [33]		550ProspectiveFETCorrelation between dynamic PET parameters and histopathological characteristics, metabolic and molecular signatures2–4
Floeth et al., 2011 * [34]30 24ProspectiveFETCorrelation between FET-PET uptake and intraoperative 5-ALA fluorescence2, 3
Ewelt et al., 2011 * [35]30 2NAProspectiveFETRelationship between FET-PET uptake, contrast-enhanced areas at MRI, and 5-ALA fluorescence intraoperatively2, 3
Arita et al., 2012 * [36]11NAProspectiveMetCorrelation between Met-PET uptake and intraoperative 5-ALA fluorescence2–4
Pafundi et al., 2013 [37]102Prospective18FDOPAHistopathological differences between CE-MRI areas and 18FDOPA areas and correlation of pathological characteristics with PET uptake and use in RT planning2–4
Beppu et al., 2015 * [38]130ProspectiveFRP170Comparison of FRP170-PET uptake areas with histological findings4
Karlberg et al., 2019 * [39]113ProspectiveF-FACBCDiagnostic value of 18F-FACBC PET/MRI in distinguishing between low-grade and high-grade gliomas and its use in guiding surgical resection2–4
Fernandez et al., 2019 *
[40]		130ProspectiveFLTAssessment of the added value of PET imaging integration to MRI in detecting tumoral tissue and correlation of PET uptake to tumor proliferation and grading4
Ponisio et al., 2020
[41]		104Prospective18FDOPAA better assessment of tumor volume and surgical margins and correlation of 18FDOPA-PET/MRI imaging with grade, histopathology, and molecular markers2–4
Verburg et al., 2020 * [42]200ProspectiveFETAssessment of best imaging studies’ (both FET-PET imaging and different MRI sequences) combination to detect glioma infiltration in enhancing and nonenhancing glioma2–4
Wakabayashi et al., 2021 *
[43]		450Multicenter, nonrandomized,
open-label phase III clinical trial		18F-fluciclovineAssessment of diagnostic accuracy of 18F-fluciclovine and useful in determining the extent of resection2–4
* They provided information on methods to decrease the influence of brain shift in the area that was planned for biopsy. 1 Preoperative PET imaging was performed in only 20 patients. 2 Both papers presented the same series of patients; 18F-RP170: 1-(2-hydroxy-1-[hydroxymethyl]ethoxy)methy l-2-nitroimidazole (RP170); 18F-FACBC: anti-1-amino-3-[18F]fluorocyclobutane-1-carboxylic acid; FETNIM: fluoroerythronitroimidazole; 18F-fluciclovine: anti-1-amino-3-[18F]fluorocyclobutane carboxylic acid or anti-[18F]FACBC.
Table
Table 2. List of references where AA-PET imaging integrated surgery for GBM was demonstrated to improve PFS and/or OS.
Table 2. List of references where AA-PET imaging integrated surgery for GBM was demonstrated to improve PFS and/or OS.
Authors, YearNo. of All Pts with HGG/No. of Primary HGGSex
(All Pts)		Age (Mean; Range)PET RadiotracersPET Resection (y/n)EOREOR Improvement (y/n)PFS (Mean and Range)OS
(Mean and Range)		Limits
Pirotte et al., 2009 1 [45]66/31 23♀; 43♂6–70FDG (n. 9), Met (n. 22)y10/31 PET-STR
21/31 PET-GTR		yNA
NA		32.8
(NA) 		3 children were included in the study;
although the difference in overall survival was statistically significant, 32.6 or 32.4, compared with 17.6 months (χ2 = 20.231 (df, 1); p = 0.0001; median survival: R = 5.714; hazard ratio, 0.532), they did not report the OS for each group considered in the comparison
Inoue et al., 2021 [28]103♀; 7♂66.4 y (38–79)Mety8/10 CE-GTR 1
2/10 CE-STR		NA17.5 mos (2.1–65)26.4 mos
(6–65)
Ort et al., 2021;
[46]		30/1611♀; 19♂59.9 y
(53–63		FETNA12/20 PET-GTR
8/20 PET-STR		yNA
NA		15.1
13.6		Impossible to extrapolate the use of PET imaging
1 GTR was considered 100% resection of tumor volume, while a subtotal resection was considered between 95% and 100%; HGG, high-grade glioma; EOR, extent of resection; PFS, progression-free survival; OS, overall survival, Met, [methyl-11C]-L-methionine; CE-GTR, contrast-enhanced gross total resection; CE-STR, contrast-enhanced subtotal resection.
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De Marco, R.; Pesaresi, A.; Bianconi, A.; Zotta, M.; Deandreis, D.; Morana, G.; Zeppa, P.; Melcarne, A.; Garbossa, D.; Cofano, F. A Systematic Review of Amino Acid PET Imaging in Adult-Type High-Grade Glioma Surgery: A Neurosurgeon’s Perspective. Cancers 2023, 15, 90. https://doi.org/10.3390/cancers15010090

AMA Style

De Marco R, Pesaresi A, Bianconi A, Zotta M, Deandreis D, Morana G, Zeppa P, Melcarne A, Garbossa D, Cofano F. A Systematic Review of Amino Acid PET Imaging in Adult-Type High-Grade Glioma Surgery: A Neurosurgeon’s Perspective. Cancers. 2023; 15(1):90. https://doi.org/10.3390/cancers15010090

Chicago/Turabian Style

De Marco, Raffaele, Alessandro Pesaresi, Andrea Bianconi, Michela Zotta, Désirée Deandreis, Giovanni Morana, Pietro Zeppa, Antonio Melcarne, Diego Garbossa, and Fabio Cofano. 2023. "A Systematic Review of Amino Acid PET Imaging in Adult-Type High-Grade Glioma Surgery: A Neurosurgeon’s Perspective" Cancers 15, no. 1: 90. https://doi.org/10.3390/cancers15010090

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