A systematic review on the use of quantitative imaging to detect cancer therapy adverse effects in normal-appearing brain tissue

Cancer therapy for both central nervous system (CNS) and non-CNS tumors has been previously associated with transient and long-term cognitive deterioration, commonly referred to as ‘chemo fog’. This therapy-related damage to otherwise normal-appearing brain tissue is reported using post-mortem neuropathological analysis. Although the literature on monitoring therapy effects on structural magnetic resonance imaging (MRI) is well established, such macroscopic structural changes appear relatively late and irreversible. Early quantitative MRI biomarkers of therapy-induced damage would potentially permit taking these treatment side effects into account, paving the way towards a more personalized treatment planning. This systematic review (PROSPERO number 224196) provides an overview of quantitative tomographic imaging methods, potentially identifying the adverse side effects of cancer therapy in normal-appearing brain tissue. Seventy studies were obtained from the MEDLINE and Web of Science databases. Studies reporting changes in normal-appearing brain tissue using MRI, PET, or SPECT quantitative biomarkers, related to radio-, chemo-, immuno-, or hormone therapy for any kind of solid, cystic, or liquid tumor were included. The main findings of the reviewed studies were summarized, providing also the risk of bias of each study assessed using a modified QUADAS-2 tool. For each imaging method, this review provides the methodological background, and the benefits and shortcomings of each method from the imaging perspective. Finally, a set of recommendations is proposed to support future research

MGMT methylation may benefit overall survival in patients with moderately vascularized glioblastomas

[EN] Objectives To assess the combined role of tumor vascularity, estimated from perfusion MRI, andMGMTmethylation status on overall survival (OS) in patients with glioblastoma. Methods A multicentric international dataset including 96 patients from NCT03439332 clinical study were used to study the prognostic relationships betweenMGMTand perfusion markers. Relative cerebral blood volume (rCBV) in the most vascularized tumor regions was automatically obtained from preoperative MRIs using ONCOhabitats online analysis service. Cox survival regression models and stratification strategies were conducted to define a subpopulation that is particularly favored byMGMTmethylation in terms of OS. Results rCBV distributions did not differ significantly (p > 0.05) in the methylated and the non-methylated subpopulations. In patients with moderately vascularized tumors (rCBV 10.73), however, there was no significant effect ofMGMTmethylation (HR = 1.72,p = 0.10, AUC = 0.56). Conclusions Our results indicate the existence of complementary prognostic information provided byMGMTmethylation and rCBV. Perfusion markers could identify a subpopulation of patients who will benefit the most fromMGMTmethylation. Not considering this information may lead to bias in the interpretation of clinical studies.Open Access funding provided by University of Oslo (incl Oslo University Hospital). This study has received funding from MTS4up project (National Plan for Scientific and Technical Research and Innovation 2013-2016, No. DPI2016-80054-R) (JMGG); H2020-SC12016-CNECT Project (No. 727560) (JMGG), H2020-SC1-BHC-20182020 (No. 825750) (JMGG), the European Research Council (ERC) under the European Union's Horizon 2020 (Grant Agreement No. 758657), the South-Eastern Norway Regional Health Authority Grants 2017073 and 2013069, the Research Council of Norway Grants 261984 (KEE). M.A.T was supported by Programa Estatal de Promocion del Talento y su Empleabilidad en I+D+i (DPI2016-80054-R). E.F.G was supported by the European Union's Horizon 2020 research and innovation programme under the Marie Sklodowska-Curie grant agreement (No. 844646).Fuster García, E.; Lorente Estellés, D.; Álvarez-Torres, MDM.; Juan-Albarracín, J.; Chelebian-Kocharyan, EA.; Rovira, A.; Auger Acosta, C.... (2021). MGMT methylation may benefit overall survival in patients with moderately vascularized glioblastomas. European Radiology. 31(3):1738-1747. https://doi.org/10.1007/s00330-020-07297-41738174731

Reevaluating the imaging definition of tumor progression: perfusion MRI quantifies recurrent glioblastoma tumor fraction, pseudoprogression, and radiation necrosis to predict survival

INTRODUCTION: Contrast-enhanced MRI (CE-MRI) represents the current mainstay for monitoring treatment response in glioblastoma multiforme (GBM), based on the premise that enlarging lesions reflect increasing tumor burden, treatment failure, and poor prognosis. Unfortunately, irradiating such tumors can induce changes in CE-MRI that mimic tumor recurrence, so called post treatment radiation effect (PTRE), and in fact, both PTRE and tumor re-growth can occur together. Because PTRE represents treatment success, the relative histologic fraction of tumor growth versus PTRE affects survival. Studies suggest that Perfusion MRI (pMRI)–based measures of relative cerebral blood volume (rCBV) can noninvasively estimate histologic tumor fraction to predict clinical outcome. There are several proposed pMRI-based analytic methods, although none have been correlated with overall survival (OS). This study compares how well histologic tumor fraction and OS correlate with several pMRI-based metrics. METHODS: We recruited previously treated patients with GBM undergoing surgical re-resection for suspected tumor recurrence and calculated preoperative pMRI-based metrics within CE-MRI enhancing lesions: rCBV mean, mode, maximum, width, and a new thresholding metric called pMRI–fractional tumor burden (pMRI-FTB). We correlated all pMRI-based metrics with histologic tumor fraction and OS. RESULTS: Among 25 recurrent patients with GBM, histologic tumor fraction correlated most strongly with pMRI-FTB (r = 0.82; P < .0001), which was the only imaging metric that correlated with OS (P<.02). CONCLUSION: The pMRI-FTB metric reliably estimates histologic tumor fraction (i.e., tumor burden) and correlates with OS in the context of recurrent GBM. This technique may offer a promising biomarker of tumor progression and clinical outcome for future clinical trials

Robust association between vascular habitats and patient prognosis in glioblastoma: an international retrospective multicenter study

This is the peer reviewed version of the following article: del Mar Álvarez-Torres, M., Juan-Albarracín, J., Fuster-Garcia, E., Bellvís-Bataller, F., Lorente, D., Reynés, G., Font de Mora, J., Aparici-Robles, F., Botella, C., Muñoz-Langa, J., Faubel, R., Asensio-Cuesta, S., García-Ferrando, G.A., Chelebian, E., Auger, C., Pineda, J., Rovira, A., Oleaga, L., Mollà-Olmos, E., Revert, A.J., Tshibanda, L., Crisi, G., Emblem, K.E., Martin, D., Due-Tønnessen, P., Meling, T.R., Filice, S., Sáez, C. and García-Gómez, J.M. (2020), Robust association between vascular habitats and patient prognosis in glioblastoma: An international multicenter study. J Magn Reson Imaging, 51: 1478-1486, which has been published in final form at https://doi.org/10.1002/jmri.26958. This article may be used for non-commercial purposes in accordance with Wiley Terms and Conditions for Self-Archiving.[EN] Background Glioblastoma (GBM) is the most aggressive primary brain tumor, characterized by a heterogeneous and abnormal vascularity. Subtypes of vascular habitats within the tumor and edema can be distinguished: high angiogenic tumor (HAT), low angiogenic tumor (LAT), infiltrated peripheral edema (IPE), and vasogenic peripheral edema (VPE). Purpose To validate the association between hemodynamic markers from vascular habitats and overall survival (OS) in glioblastoma patients, considering the intercenter variability of acquisition protocols. Study Type Multicenter retrospective study. Population In all, 184 glioblastoma patients from seven European centers participating in the NCT03439332 clinical study. Field Strength/Sequence 1.5T (for 54 patients) or 3.0T (for 130 patients). Pregadolinium and postgadolinium-based contrast agent-enhanced T-1-weighted MRI, T-2- and FLAIR T-2-weighted, and dynamic susceptibility contrast (DSC) T-2* perfusion. Assessment We analyzed preoperative MRIs to establish the association between the maximum relative cerebral blood volume (rCBV(max)) at each habitat with OS. Moreover, the stratification capabilities of the markers to divide patients into "vascular" groups were tested. The variability in the markers between individual centers was also assessed. Statistical Tests Uniparametric Cox regression; Kaplan-Meier test; Mann-Whitney test. Results The rCBV(max) derived from the HAT, LAT, and IPE habitats were significantly associated with patient OS (P < 0.05; hazard ratio [HR]: 1.05, 1.11, 1.28, respectively). Moreover, these markers can stratify patients into "moderate-" and "high-vascular" groups (P < 0.05). The Mann-Whitney test did not find significant differences among most of the centers in markers (HAT: P = 0.02-0.685; LAT: P = 0.010-0.769; IPE: P = 0.093-0.939; VPE: P = 0.016-1.000). Data Conclusion The rCBV(max) calculated in HAT, LAT, and IPE habitats have been validated as clinically relevant prognostic biomarkers for glioblastoma patients in the pretreatment stage. This study demonstrates the robustness of the hemodynamic tissue signature (HTS) habitats to assess the GBM vascular heterogeneity and their association with patient prognosis independently of intercenter variability. Technical Efficacy Stage: 2 J. Magn. Reson. Imaging 2019.This work was partially supported by: MTS4up project (National Plan for Scientific and Technical Research and Innovation 2013-2016, No. DPI2016-80054-R) (to J.M.G.G.); H2020-SC1-2016-CNECT Project (No. 727560) (to J.M.G.G.) and H2020-SC1-BHC-2018-2020 (No. 825750) (to J.M.G.G.); M.A.T was supported by DPI2016-80054-R (Programa Estatal de Promocion del Talento y su Empleabilidad en I + D + i). The data acquisition and curation of the Oslo University Hospital was supported by: the European Research Council (ERC) under the European Union's Horizon 2020 (Grant Agreement No. 758657), the South-Eastern Norway Regional Health Authority Grants 2017073 and 2013069, and the Research Council of Norway Grants 261984 (to K.E.E.). We gratefully acknowledge the support of NVIDIA Corporation with the donation of the Titan V GPU used for this research. E.F.G. was supported by the European Union's Horizon 2020 research and innovation programme under the Marie Sklodowska-Curie grant agreement No. 844646. Figure 1 was designed by the Science Artist Elena Poritskaya.Álvarez-Torres, MDM.; Juan-Albarracín, J.; Fuster García, E.; Bellvís-Bataller, F.; Lorente, D.; Reynés, G.; Font De Mora, J.... (2020). Robust association between vascular habitats and patient prognosis in glioblastoma: an international retrospective multicenter study. Journal of Magnetic Resonance Imaging. 51(5):1478-1486. https://doi.org/10.1002/jmri.2695814781486515Louis, D. N., Perry, A., Reifenberger, G., von Deimling, A., Figarella-Branger, D., Cavenee, W. K., … Ellison, D. W. (2016). The 2016 World Health Organization Classification of Tumors of the Central Nervous System: a summary. Acta Neuropathologica, 131(6), 803-820. doi:10.1007/s00401-016-1545-1Gately, L., McLachlan, S., Dowling, A., & Philip, J. (2017). 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M., Gutman, D., Scarpace, L., Hwang, S. N., Holder, C. A., … Flanders, A. (2014). Outcome Prediction in Patients with Glioblastoma by Using Imaging, Clinical, and Genomic Biomarkers: Focus on the Nonenhancing Component of the Tumor. Radiology, 272(2), 484-493. doi:10.1148/radiol.14131691Jensen, R. L., Mumert, M. L., Gillespie, D. L., Kinney, A. Y., Schabel, M. C., & Salzman, K. L. (2013). Preoperative dynamic contrast-enhanced MRI correlates with molecular markers of hypoxia and vascularity in specific areas of intratumoral microenvironment and is predictive of patient outcome. Neuro-Oncology, 16(2), 280-291. doi:10.1093/neuonc/not148Jena, A., Taneja, S., Gambhir, A., Mishra, A. K., D’souza, M. M., Verma, S. M., … Sogani, S. K. (2016). Glioma Recurrence Versus Radiation Necrosis. Clinical Nuclear Medicine, 41(5), e228-e236. doi:10.1097/rlu.0000000000001152Price, S. J., Young, A. M. H., Scotton, W. J., Ching, J., Mohsen, L. A., Boonzaier, N. R., … Larkin, T. J. (2015). Multimodal MRI can identify perfusion and metabolic changes in the invasive margin of glioblastomas. Journal of Magnetic Resonance Imaging, 43(2), 487-494. doi:10.1002/jmri.24996Chang, Y.-C. C., Ackerstaff, E., Tschudi, Y., Jimenez, B., Foltz, W., Fisher, C., … Stoyanova, R. (2017). Delineation of Tumor Habitats based on Dynamic Contrast Enhanced MRI. Scientific Reports, 7(1). doi:10.1038/s41598-017-09932-5Cui, Y., Tha, K. K., Terasaka, S., Yamaguchi, S., Wang, J., Kudo, K., … Li, R. (2016). Prognostic Imaging Biomarkers in Glioblastoma: Development and Independent Validation on the Basis of Multiregion and Quantitative Analysis of MR Images. Radiology, 278(2), 546-553. doi:10.1148/radiol.2015150358Juan-Albarracín, J., Fuster-Garcia, E., Pérez-Girbés, A., Aparici-Robles, F., Alberich-Bayarri, Á., Revert-Ventura, A., … García-Gómez, J. M. (2018). Glioblastoma: Vascular Habitats Detected at Preoperative Dynamic Susceptibility-weighted Contrast-enhanced Perfusion MR Imaging Predict Survival. Radiology, 287(3), 944-954. doi:10.1148/radiol.2017170845Fuster-Garcia, E., Juan-Albarracín, J., García-Ferrando, G. A., Martí-Bonmatí, L., Aparici-Robles, F., & García-Gómez, J. M. (2018). Improving the estimation of prognosis for glioblastoma patients by MR based hemodynamic tissue signatures. NMR in Biomedicine, 31(12), e4006. doi:10.1002/nbm.4006Abramson, R. G., Burton, K. R., Yu, J.-P. J., Scalzetti, E. M., Yankeelov, T. E., Rosenkrantz, A. B., … Subramaniam, R. M. (2015). Methods and Challenges in Quantitative Imaging Biomarker Development. Academic Radiology, 22(1), 25-32. doi:10.1016/j.acra.2014.09.001Stupp, R., Mason, W. P., van den Bent, M. J., Weller, M., Fisher, B., Taphoorn, M. J. B., … Mirimanoff, R. O. (2005). Radiotherapy plus Concomitant and Adjuvant Temozolomide for Glioblastoma. 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Differentiation between vasogenic-edema versus tumor-infiltrative area in patients with glioblastoma during bevacizumab therapy: A longitudinal MRI study. European Journal of Radiology, 83(7), 1250-1256. doi:10.1016/j.ejrad.2014.03.02

Repeatability of Cerebral Perfusion Using Dynamic Susceptibility Contrast MRI in Glioblastoma Patients12

OBJECTIVES This study evaluates the repeatability of brain perfusion using dynamic susceptibility contrast magnetic resonance imaging (DSC-MRI) with a variety of post-processing methods. METHODS Thirty-two patients with newly diagnosed glioblastoma were recruited. On a 3-T MRI using a dual-echo, gradient-echo spin-echo DSC-MRI protocol, the patients were scanned twice 1 to 5 days apart. Perfusion maps including cerebral blood volume (CBV) and cerebral blood flow (CBF) were generated using two contrast agent leakage correction methods, along with testing normalization to reference tissue, and application of arterial input function (AIF). Repeatability of CBV and CBF within tumor regions and healthy tissues, identified by structural images, was assessed with intra-class correlation coefficients (ICCs) and repeatability coefficients (RCs). Coefficients of variation (CVs) were reported for selected methods. RESULTS CBV and CBF were highly repeatable within tumor with ICC values up to 0.97. However, both CBV and CBF showed lower ICCs for healthy cortical tissues (up to 0.83), healthy gray matter (up to 0.95), and healthy white matter (WM; up to 0.93). The values of CV ranged from 6% to 10% in tumor and 3% to 11% in healthy tissues. The values of RC relative to the mean value of measurement within healthy WM ranged from 22% to 42% in tumor and 7% to 43% in healthy tissues. These percentages show how much variation in perfusion parameter, relative to that in healthy WM, we expect to observe to consider it statistically significant. We also found that normalization improved repeatability, but AIF deconvolution did not. CONCLUSIONS DSC-MRI is highly repeatable in high-grade glioma patients

Automatic segmentation of meningioma from non-contrasted brain MRI integrating fuzzy clustering and region growing

<p>Abstract</p> <p>Background</p> <p>In recent years, magnetic resonance imaging (MRI) has become important in brain tumor diagnosis. Using this modality, physicians can locate specific pathologies by analyzing differences in tissue character presented in different types of MR images.</p> <p>This paper uses an algorithm integrating fuzzy-c-mean (FCM) and region growing techniques for automated tumor image segmentation from patients with menigioma. Only non-contrasted T1 and T2 -weighted MR images are included in the analysis. The study's aims are to correctly locate tumors in the images, and to detect those situated in the midline position of the brain.</p> <p>Methods</p> <p>The study used non-contrasted T1- and T2-weighted MR images from 29 patients with menigioma. After FCM clustering, 32 groups of images from each patient group were put through the region-growing procedure for pixels aggregation. Later, using knowledge-based information, the system selected tumor-containing images from these groups and merged them into one tumor image. An alternative semi-supervised method was added at this stage for comparison with the automatic method. Finally, the tumor image was optimized by a morphology operator. Results from automatic segmentation were compared to the "ground truth" (GT) on a pixel level. Overall data were then evaluated using a quantified system.</p> <p>Results</p> <p>The quantified parameters, including the "percent match" (PM) and "correlation ratio" (CR), suggested a high match between GT and the present study's system, as well as a fair level of correspondence. The results were compatible with those from other related studies. The system successfully detected all of the tumors situated at the midline of brain.</p> <p>Six cases failed in the automatic group. One also failed in the semi-supervised alternative. The remaining five cases presented noticeable edema inside the brain. In the 23 successful cases, the PM and CR values in the two groups were highly related.</p> <p>Conclusions</p> <p>Results indicated that, even when using only two sets of non-contrasted MR images, the system is a reliable and efficient method of brain-tumor detection. With further development the system demonstrates high potential for practical clinical use.</p

Early changes in glioblastoma metabolism measured by MR spectroscopic imaging during combination of anti-angiogenic cediranib and chemoradiation therapy are associated with survival

Precise assessment of treatment response in glioblastoma during combined anti-angiogenic and chemoradiation remains a challenge. In particular, early detection of treatment response by standard anatomical imaging is confounded by pseudo-response or pseudo-progression. Metabolic changes may be more specific for tumor physiology and less confounded by changes in blood-brain barrier permeability. We hypothesize that metabolic changes probed by magnetic resonance spectroscopic imaging can stratify patient response early during combination therapy. We performed a prospective longitudinal imaging study in newly diagnosed glioblastoma patients enrolled in a phase II clinical trial of the pan-vascular endothelial growth factor receptor inhibitor cediranib in combination with standard fractionated radiation and temozolomide (chemoradiation). Forty patients were imaged weekly during therapy with an imaging protocol that included magnetic resonance spectroscopic imaging, perfusion magnetic resonance imaging, and anatomical magnetic resonance imaging. Data were analyzed using receiver operator characteristics, Cox proportional hazards model, and Kaplan-Meier survival plots. We observed that the ratio of total choline to healthy creatine after 1 month of treatment was significantly associated with overall survival, and provided as single parameter: (1) the largest area under curve (0.859) in receiver operator characteristics, (2) the highest hazard ratio (HR = 85.85, P = 0.006) in Cox proportional hazards model, (3) the largest separation (P = 0.004) in Kaplan-Meier survival plots. An inverse correlation was observed between total choline/healthy creatine and cerebral blood flow, but no significant relation to tumor volumetrics was identified. Our results suggest that in vivo metabolic biomarkers obtained by magnetic resonance spectroscopic imaging may be an early indicator of response to anti-angiogenic therapy combined with standard chemoradiation in newly diagnosed glioblastoma

Advanced MR techniques for preoperative glioma characterization: Part 1

Preoperative clinical magnetic resonance imaging (MRI) protocols for gliomas, brain tumors with dismal outcomes due to their infiltrative properties, still rely on conventional structural MRI, which does not deliver information on tumor genotype and is limited in the delineation of diffuse gliomas. The GliMR COST action wants to raise awareness about the state of the art of advanced MRI techniques in gliomas and their possible clinical translation or lack thereof. This review describes current methods, limits, and applications of advanced MRI for the preoperative assessment of glioma, summarizing the level of clinical validation of different techniques. In this first part, we discuss dynamic susceptibility contrast and dynamic contrast-enhanced MRI, arterial spin labeling, diffusion-weighted MRI, vessel imaging, and magnetic resonance fingerprinting. The second part of this review addresses magnetic resonance spectroscopy, chemical exchange saturation transfer, susceptibility-weighted imaging, MRI-PET, MR elastography, and MR-based radiomics applications. Evidence Level: 3 Technical Efficacy: Stage 2

Standardized postnatal management of infants with congenital diaphragmatic hernia in Europe: The CDH EURO Consortium Consensus - 2015 Update

In 2010, the congenital diaphragmatic hernia (CDH) EURO Consortium published a standardized neonatal treatment protocol. Five years later, the number of participating centers has been raised from 13 to 22. In this article the relevant literature is updated, and consensus has been reached between the members of the CDH EURO Consortium. Key updated recommendations are: (1) planned delivery after a gestational age of 39 weeks in a high-volume tertiary center; (2) neuromuscular blocking agents to be avoided during initial treatment in the delivery room; (3) adapt treatment to reach a preductal saturation of between 80 and 95% and postductal saturation >70%; (4) target PaCO2 to be between 50 and 70 mm Hg; (5) conventional mechanical ventilation to be the optimal initial ventilation strategy, and (6) intravenous sildenafil to be considered in CDH patients with severe pulmonary hypertension. This article represents the current opinion of all consortium members in Europe for the optimal neonatal treatment of CDH

The Open Brain Consent: Informing research participants and obtaining consent to share brain imaging data

Having the means to share research data openly is essential to modern science. For human research, a key aspect in this endeavor is obtaining consent from participants, not just to take part in a study, which is a basic ethical principle, but also to share their data with the scientific community. To ensure that the participants' privacy is respected, national and/or supranational regulations and laws are in place. It is, however, not always clear to researchers what the implications of those are, nor how to comply with them. The Open Brain Consent (https://open-brain-consent.readthedocs.io) is an international initiative that aims to provide researchers in the brain imaging community with information about data sharing options and tools. We present here a short history of this project and its latest developments, and share pointers to consent forms, including a template consent form that is compliant with the EU general data protection regulation. We also share pointers to an associated data user agreement that is not only useful in the EU context, but also for any researchers dealing with personal (clinical) data elsewhere