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letter
. 2020 Jul 31;22(11):1705. doi: 10.1093/neuonc/noaa176

Letter regarding “Consensus recommendations for a standardized brain tumor imaging protocol for clinical trials in brain metastases”

Estanislao Arana 1,, Leoncio A Arribas 2
PMCID: PMC7690351  PMID: 32735663

We have read with interest “Consensus Recommendations for a Standardized Brain Tumor Imaging Protocol for Clinical Trials in Brain Metastases” by Kaufmann et al.1 We welcome the suggestion to replace IR-GRE (ionizing radiation‒gradient recalled echo) sequences for 3D TSE (turbo spin echo) T1. However, we strongly disagree with their recommendation for 3T imaging due to the reasons hereby exposed:

  • • Systematic review has shown that 3T is not superior to 1.5T on clinical outcomes. A small proportion of very small (<5 mm diameter) metastases were only detected at 3T, whereas no difference was shown in lesions >5 mm.2 This 5 mm is the size limit of measurable disease according to Response Assessment in Neuro-Oncology Brain Metastases guidelines.

  • • Even on clinical practice previous to stereotactic radiosurgery, despite the large number of brain metastases depicted by 3T, there was no statistical significance.3 Regrettably, it is beyond the limitations of references in this letter, but there are studies comparing different 3D sequences on 1.5T.

  • • 1.5T imaging is more robust in treatment planning for radiation oncology due to potential increased distortions associated with 3T. The quality assurance measures for radiosurgical planning must be extremely stringent in general but more so with 3T imaging.

Concerning radiation necrosis diagnosis, a fundamental message is missing: the majority of them are asymptomatic. Therefore, strict correlation with anamnesis and neurological exploration is mandatory.

We applaud their encouragment of dynamic susceptibility MRI, widely available in almost every scanner. Albeit, it goes without mention that dynamic contrast enhanced MRI has been shown to be superior against PET-fluorodeoxyglucose (FDG) in a clinical trial for diagnosing recurrence versus radiation necrosis.4 Regarding PET imaging, we must stress caution ahead with amino acid PETs; their accuracies are not superior to FDG in recent systematic reviews.5

Finally, radiomic and deep learning are in their beginnings. The mentioned tailored one-radiomic approach performed worse in metastatic tumors than in primary brain tumors. There are other radiomic approaches based on open source software.6

References

  • 1. Kaufmann TJ, Smits M, Boxerman J, et al.  Consensus recommendations for a standardized brain tumor imaging protocol for clinical trials in brain metastases. Neuro Oncol. 2020;22(6):757–772. [DOI] [PMC free article] [PubMed] [Google Scholar]
  • 2. Wardlaw JM, Brindle W, Casado AM, et al. ; SINAPSE Collaborative Group A systematic review of the utility of 1.5 versus 3 Tesla magnetic resonance brain imaging in clinical practice and research. Eur Radiol. 2012;22(11):2295–2303. [DOI] [PubMed] [Google Scholar]
  • 3. Wardak Z, Augustyn A, Zhu H, et al.  Pre-treatment factors associated with detecting additional brain metastases at stereotactic radiosurgery. J Neurooncol. 2016;128(2):251–257. [DOI] [PubMed] [Google Scholar]
  • 4. Hatzoglou V, Yang TJ, Omuro A, et al.  A prospective trial of dynamic contrast-enhanced MRI perfusion and fluorine-18 FDG PET-CT in differentiating brain tumor progression from radiation injury after cranial irradiation. Neuro Oncol. 2016;18(6):873–880. [DOI] [PMC free article] [PubMed] [Google Scholar]
  • 5. Treglia G, Muoio B, Trevisi G, et al.  Diagnostic performance and prognostic value of PET/CT with different tracers for brain tumors: a systematic review of published meta-analyses. Int J Mol Sci. 2019;20(19):4669. [DOI] [PMC free article] [PubMed] [Google Scholar]
  • 6. Larroza A, Moratal D, Paredes-Sánchez A, et al.  Support vector machine classification of brain metastasis and radiation necrosis based on texture analysis in MRI. J Magn Reson Imaging. 2015;42(5):1362–1368. [DOI] [PubMed] [Google Scholar]

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