Photon vs. proton radiochemotherapy: Effects on brain tissue volume and perfusion

Petr, Jan; Platzek, Ivan; Hofheinz, Frank; Mutsaerts, Henk‐Jan; Asllani, Iris; Osch, Matthias J.P. van; Seidlitz, Annekatrin; Krukowski, Pawel; Gommlich, Andreas; Beuthien‐Baumann, Bettina; Jentsch, Christina; Maus, Jens; Troost, Esther G.C.; Baumann, Michaël; Krause, Mechthild; Hoff, Jörg van den

doi:10.1016/j.radonc.2017.11.033

Cited by 51 publications

(45 citation statements)

References 39 publications

(45 reference statements)

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“…To the best of our knowledge, we are the first to report a perfusion decrease independent of radiation dose in GM using DSC. Several publications have shown that grey matter volume decreases after fractionated radiotherapy increasing with radiation dose 46 , 47 , 48 , 49 , since both CBV and CBF are tissue volume dependent parameters, we believe that the dose-independency found in grey matter is a result of decreased grey matter volume instead of an actual response in CBV and CBF independent on radiation dose given.…”

Section: Discussionmentioning

confidence: 68%

Perfusion magnetic resonance imaging changes in normal appearing brain tissue after radiotherapy in glioblastoma patients may confound longitudinal evaluation of treatment response

Fahlström

Blomquist

Nyholm

et al. 2018

Radiology and Oncology

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BackgroundThe aim of this study was assess acute and early delayed radiation-induced changes in normal-appearing brain tissue perfusion as measured with perfusion magnetic resonance imaging (MRI) and the dependence of these changes on the fractionated radiotherapy (FRT) dose level.Patients and methodsSeventeen patients with glioma WHO grade III-IV treated with FRT were included in this prospective study, seven were excluded because of inconsistent FRT protocol or missing examinations. Dynamic susceptibility contrast MRI and contrast-enhanced 3D-T1-weighted (3D-T1w) images were acquired prior to and in average (standard deviation): 3.1 (3.3), 34.4 (9.5) and 103.3 (12.9) days after FRT. Pre-FRT 3D-T1w images were segmented into white- and grey matter. Cerebral blood volume (CBV) and cerebral blood flow (CBF) maps were calculated and co-registered patient-wise to pre-FRT 3D-T1w images. Seven radiation dose regions were created for each tissue type: 0–5 Gy, 5–10 Gy, 10–20 Gy, 20–30 Gy, 30–40 Gy, 40–50 Gy and 50–60 Gy. Mean CBV and CBF were calculated in each dose region and normalised (nCBV and nCBF) to the mean CBV and CBF in 0-5 Gy white- and grey matter reference regions, respectively.ResultsRegional and global nCBV and nCBF in white- and grey matter decreased after FRT, followed by a tendency to recover. The response of nCBV and nCBF was dose-dependent in white matter but not in grey matter.ConclusionsOur data suggest that radiation-induced perfusion changes occur in normal-appearing brain tissue after FRT. This can cause an overestimation of relative tumour perfusion using dynamic susceptibility contrast MRI, and can thus confound tumour treatment evaluation.

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Section: Discussionmentioning

confidence: 68%

Perfusion magnetic resonance imaging changes in normal appearing brain tissue after radiotherapy in glioblastoma patients may confound longitudinal evaluation of treatment response

Fahlström

Blomquist

Nyholm

et al. 2018

Radiology and Oncology

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“…The first time point is used as a reference for both within- and between-subject registration. However, this requires further validation in the presence of large brain deformations between sessions, such as tumors, resections, or infarcts (Petr et al 2018).…”

Section: Theory: Implementationmentioning

confidence: 99%

“…Instead in some studies, GM volume is used as a covariate in the statistical analysis (Chen et al 2011). Note that while PVC, in theory, corrects only for the PV effects and takes into account the intra- and inter-subject variability of the GM-WM CBF ratio, GM covariation can additionally affect the estimated physiological correlation between GM CBF and GM volume (Petr et al 2018).…”

Section: Theory: Implementationmentioning

confidence: 99%

ExploreASL: an image processing pipeline for multi-center ASL perfusion MRI studies

Mutsaerts

Petr

Groot

et al. 2019

Preprint

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Keywords 27 arterial spin labeling; image processing; multi-center; cerebral perfusion; quality control 28 3 Abstract 1 Arterial spin labeling (ASL) has undergone significant development since its inception, with a focus 2 on improving standardization and reproducibility of its acquisition and quantification. In a 3 community-wide effort towards robust and reproducible clinical ASL image processing, we 4 developed the software package ExploreASL, allowing standardized analyses across centers and 5 scanners. 6The procedures used in ExploreASL capitalize on published image processing advancements and 7 address the challenges of multi-center datasets with scanner-specific processing and artifact 8 reduction to limit patient exclusion. ExploreASL is self-contained, written in MATLAB and based 9 on Statistical Parameter Mapping (SPM) and runs on multiple operating systems. The toolbox 10 adheres to previously defined international standards for data structure, provenance, and best 11 analysis practice. 12ExploreASL was iteratively refined and tested in the analysis of >10,000 ASL scans using different 13 pulse-sequences in a variety of clinical populations, resulting in four processing modules: Import, 14Structural, ASL, and Population that perform tasks, respectively, for data curation, structural and 15 ASL image processing and quality control, and finally preparing the results for statistical analyses 16 on both single-subject and group level. We illustrate ExploreASL processing results from three 17 cohorts: perinatally HIV-infected children, healthy adults, and elderly at risk for 18 neurodegenerative disease. We show the reproducibility for each cohort when processed at 19 different centers with different operating systems and MATLAB versions, and its effects on the 20 quantification of gray matter cerebral blood flow. 21ExploreASL facilitates the standardization of image processing and quality control, allowing the 22 pooling of cohorts to increase statistical power and discover between-group perfusion 23 differences. Ultimately, this workflow may advance ASL for wider adoption in clinical studies, 24 trials, and practice. 25

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“…Patient's age at the preoperative period and tumor location are some of the current factors that determine the prognosis. In adult age groups, the incidence of high-grade glial tumors increases (3)(4)(5). Advanced age, especially over 70, is seen as a sign of poor prognosis.…”

Section: Introductionmentioning

confidence: 99%

Retrospective Analysis of Tumor Location with Residue Rates in High-grade Glial Tumors

Seyithanoğlu¹,

Dündar²,

Kitiş³

et al. 2020

eamr

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Glioblastoma is the most commonly seen and quite an aggressive type of primary brain tumor. Location of the tumor, age, and sex are important prognostic factors. The aim of this study was to present the retrospective data about glioblastoma patients in which location of glioblastoma and calculation of residual tumor tissue was performed at our clinic. Methods: Tumor location, age and sex distributions, and residue presence in control magnetic resonance imaging (MRI) of 99 patients treated at our clinic within the last two years with a high-grade glial tumor were examined retrospectively. Variables included in the analysis were demographic data and the presence of residue on the control MRI within 24 hours. Chi-square test was used for comparisons. The data were analyzed by SPSS version 24.0 package program. Results: Of a total of 99 glioblastomas, the male/female ratio was 2:1, the average age of the patients was 54±37 (minimum: 18, maximum: 88; standard deviation: 15.08). In MRI, tumor was located at the frontal and temporal lobes with maximal percentile. In 55 of the cases, total resection was seen. In 38 of the cases, residue under 10% was seen, and in 6 of the cases, residual mass over 10% was seen. Relationship of tumor location with residual mass was not statistically significant (p=0.562). Conclusion: The aim of neurosurgery in glioblastomas is surgical excision to remove as much tumor as possible with minimal neurological deficit. Preoperative characterization of the tumor through current imaging methods makes a significant contribution to mortality and morbidity. New prognostic parameters are needed based on new surgical approaches and imaging techniques.

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Photon vs. proton radiochemotherapy: Effects on brain tissue volume and perfusion

Cited by 51 publications

References 39 publications

Perfusion magnetic resonance imaging changes in normal appearing brain tissue after radiotherapy in glioblastoma patients may confound longitudinal evaluation of treatment response

Perfusion magnetic resonance imaging changes in normal appearing brain tissue after radiotherapy in glioblastoma patients may confound longitudinal evaluation of treatment response

ExploreASL: an image processing pipeline for multi-center ASL perfusion MRI studies

Retrospective Analysis of Tumor Location with Residue Rates in High-grade Glial Tumors

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