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The alleviation of hypoxia in glioblastoma with carbogen to improve treatment has met with limited success. Our hypothesis is that the eventual benefits of carbogen depend on the capacity for vasodilation. We examined, with MRI, changes in fractional cerebral blood volume, blood oxygen saturation, and blood oxygenation level dependent signals in response to carbogen. The analyses were performed in two xenograft models of glioma (U87 and U251) recognized to have different vascular patterns. Carbogen increased fractional cerebral blood volume, blood oxygen saturation, and blood oxygenation level dependent signals in contralateral tissues. In the tumor core and peritumoral regions, changes were dependent on the capacity to vasodilate rather than on resting fractional cerebral blood volume. In the highly vascularised U87 tumor, carbogen induced a greater increase in fractional cerebral blood volume and blood oxygen saturation in comparison to the less vascularized U251 tumor. The blood oxygenation level dependent signal revealed a delayed response in U251 tumors relative to the contralateral tissue. Additionally, we highlight the considerable heterogeneity of fractional cerebral blood volume, blood oxygen saturation, and blood oxygenation level dependent within U251 tumor in which multiple compartments co-exist (tumor core, rim and peritumoral regions). Finally, our study underlines the complexity of the flow/metabolism interactions in different models of glioblastoma. These irregularities should be taken into account in order to palliate intratumoral hypoxia in clinical trials.

Objective: Neuroblastoma has one of the lowest survival rates of all childhood cancers, despite the use of intensive treatment regimens. Preclinical models of neuroblastoma are essential for testing new multimodality protocols, including those that involve radiotherapy (RT). The aim of this study was to develop a robust method for RT planning and tumour response monitoring based on combined MRI and cone-beam CT (CBCT) imaging and to apply it to a widely studied mouse xenograft model of neuroblastoma, SK-N-SH., Methods: As part of a tumour growth inhibition study, SK-N-SH xenografts were generated in BALB/c nu/nu mice. Mice (n = 8) were placed in a printed MR- and CT-compatible plastic cradle, imaged using a 4.7-T MRI scanner and then transferred to a small animal radiation research platform (SARRP) irradiator with on-board CBCT. MRI/CBCT co-registration was performed to enable RT planning using the soft-tissue contrast afforded by MRI prior to delivery of RT (5 Gy). Tumour response was assessed by serial MRI and calliper measurements., Results: SK-N-SH xenografts formed soft, deformable tumours that could not be differentiated from surrounding normal tissues using CBCT. MR images, which allowed clear delineation of tumours, were successfully co-registered with CBCT images, allowing conformal RT to be delivered. MRI measurements of tumour volume 4 days after RT correlated strongly with length of survival time., Conclusion: MRI allowed precision RT of SK-N-SH tumours and provided an accurate means of measuring tumour response. Advances in knowledge: MRI-based RT planning of murine tumours is feasible using an SARRP irradiator.

Purpose: The primary objective of this study was to compare the ability of PET and MRI biomarkers to predict treatment efficacy in a preclinical model of recurrent glioblastoma multiforme., Methods: MRI (anatomical, diffusion, vasculature and oxygenation) and PET ([(18)F]FDG and [(18)F]FLT) parameters were obtained 3 days after the end of treatment and compared with late tumour growth and survival., Results: Early after tumour recurrence, no effect of treatment with temozolomide combined with bevacizumab was observed on tumour volume as assessed by T2-W MRI. At later times, the treatment decreased tumour volume and increased survival. Interestingly, at the earlier time, temozolomide + bevacizumab decreased [(18)F]FLT uptake, cerebral blood volume and oedema. [(18)F]FLT uptake, oedema and cerebral blood volume were correlated with overall survival but [(18)F]FLT uptake had the highest specificity and sensitivity for the early prediction of treatment efficacy., Conclusion: The present investigation in a preclinical model of glioblastoma recurrence underscores the importance of multimodal imaging in the assessment of oedema, tumour vascular status and cell proliferation. Finally, [(18)F]FLT holds the greatest promise for the early assessment of treatment efficacy. These findings may translate clinically in that individualized treatment for recurrent glioma could be prescribed for patients selected after PET/MRI examinations.

The individualized care of glioma patients ought to benefit from imaging biomarkers as precocious predictors of therapeutic efficacy. Contrast enhanced MRI and [(18)F]-fluorodeoxyglucose (FDG)-PET are routinely used in clinical settings; their ability to forecast the therapeutic response is controversial. The objectives of our preclinical study were to analyze sensitive µMRI and/or µPET imaging biomarkers to predict the efficacy of anti-angiogenic and/or chemotherapeutic regimens. Human U87 and U251 orthotopic glioma models were implanted in nude rats. Temozolomide and/or bevacizumab were administered. µMRI (anatomical, diffusion, and microrheological parameters) and µPET ([(18)F]-FDG and [(18)F]-fluoro-l-thymidine [FLT]-PET) studies were undertaken soon (t(1)) after treatment initiation compared with late anatomical µMRI evaluation of tumor volume (t(2)) and overall survival. In both models, FDG and FLT uptakes were attenuated at t(1) in response to temozolomide alone or with bevacizumab. The distribution of FLT, reflecting intratumoral heterogeneity, was also modified. FDG was less predictive for treatment efficacy than was FLT (also highly correlated with outcome, P < .001 for both models). Cerebral blood volume was significantly decreased by temozolomide + bevacizumab and was correlated with survival for rats with U87 implants. While FLT was highly predictive of treatment efficacy, a combination of imaging biomarkers was superior to any one alone (P < .0001 in both tumors with outcome). Our results indicate that FLT is a sensitive predictor of treatment efficacy and that predictability is enhanced by a combination of imaging biomarkers. These findings may translate clinically in that individualized glioma treatments could be decided in given patients after PET/MRI examinations.

Background: Brain metastases (BM) are the most frequent malignant brain tumors. The aim of this study was to characterize the tumor microenvironment (TME) of BM and particularly hypoxia and redox state, known to play a role in tumor growth and treatment resistance with multimodal PET and MRI imaging, immunohistochemical and proteomic approaches in a human lung cancer (H2030-BrM3)-derived BM model in rats. Results: First, in vitro studies confirmed that H2030-BrM3 cells respond to hypoxia with increasing expression of HIF-1, HIF-2 and their target genes. Proteomic analyses revealed, among expression changes, proteins associated with metabolism, oxidative stress, metal response and hypoxia signaling in particular in cortical BM. [64Cu][Cu(ATSM)] PET revealed a significant uptake by cortical BM (p < 0.01), while no uptake is observed in striatal BM 23 days after tumor implantation. Pimonidazole, HIF-1α, HIF-2α, CA-IX as well as GFAP, CTR1 and DMT1 immunostainings are positive in both BM. Conclusion: Overall, [64Cu][Cu(ATSM)] imaging and proteomic results showed the presence of hypoxia and protein expression changes linked to hypoxia and oxidative stress in BM, which are more pronounced in cortical BM compared to striatal BM. Moreover, it emphasized the interest of [64Cu][Cu(ATSM)] PET to characterize TME of BM and depict inter-metastasis heterogeneity that could be useful to guide treatments. [ABSTRACT FROM AUTHOR]

Acute ischemic stroke results in an ischemic core surrounded by a tissue at risk, named the penumbra, which is potentially salvageable. One way to differentiate the tissues is to measure the hypoxia status. The purpose of the current study is to correlate the abnormal brain tissue volume derived from magnetic resonance‐based imaging of brain oxygen saturation (StO2‐MRI) to the fluorine‐18 fluoromisonidazole ([18F]FMISO) positron emission tomography (PET) volume for hypoxia imaging validation, and to analyze the ability of StO2‐MRI to depict the different hypoxic tissue types in the acute phase of stroke. In a pertinent model of stroke in the rat, the volume of tissue with decreased StO2‐MRI signal and that with increased uptake of [18F]FMISO were equivalent and correlated (r = 0.706; p = 0.015). The values of StO2 in the tissue at risk were significantly greater than those quantified in the core of the lesion, and were less than those for healthy tissue (52.3% ± 2.0%; 43.3% ± 1.9%, and 67.9 ± 1.4%, respectively). A threshold value for StO2 of ≈60% as the cut‐off for the identification of the tissue at risk was calculated. Tissue volumes with reduced StO2‐MRI correlated with the final lesion (r = 0.964, p < 0.0001). The findings show that the StO2‐MRI approach is sensitive for the detection of hypoxia and for the prediction of the final lesion after stroke. Once validated in acute clinical settings, this approach might be used to enhance the stratification of patients for potential therapeutic interventions. [ABSTRACT FROM AUTHOR]

Lung cancer patients frequently develop brain metastases (BM). Despite aggressive treatment including neurosurgery and external-radiotherapy, overall survival remains poor. There is a pressing need to further characterize factors in the microenvironment of BM that may confer resistance to radiotherapy (RT), such as hypoxia. Here, hypoxia was first evaluated in 28 biopsies from patients with non‑small cell lung cancer (NSCLC) BM, using CA-IX immunostaining. Hypoxia characterization (pimonidazole, CA-IX and HIF-1α) was also performed in different preclinical NSCLC BM models induced either by intracerebral injection of tumor cells (H2030-Br3M, H1915) into the cortex and striatum, or intracardial injection of tumor cells (H2030-Br3M). Additionally, [18F]-FMISO-PET and oxygen-saturation-mapping-MRI (SatO2-MRI) were carried out in the intracerebral BM models to further characterize tumor hypoxia and evaluate the potential of Hypoxia-image-guided-RT (HIGRT). The effect of RT on proliferation of BM ([18F]-FLT-PET), tumor volume and overall survival was determined. We showed that hypoxia is a major yet heterogeneous feature of BM from lung cancer both preclinically and clinically. HIGRT, based on hypoxia heterogeneity observed between cortical and striatal metastases in the intracerebrally induced models, showed significant potential for tumor control and animal survival. These results collectively highlight hypoxia as a hallmark of BM from lung cancer and the value of HIGRT in better controlling tumor growth. [ABSTRACT FROM AUTHOR]

The partial pressure in oxygen remains challenging to map in the brain. Two main strategies exist to obtain surrogate measures of tissue oxygenation: the tissue saturation studied by magnetic resonance imaging (StO2-MRI) and the identification of hypoxia by a positron emission tomography (PET) biomarker with 3-[18F]fluoro-1-(2-nitro-1-imidazolyl)-2-propanol ([18F]-FMISO) as the leading radiopharmaceutical. Nonetheless, a formal validation of StO2-MRI against FMISO-PET has not been performed. The objective of our studies was to compare the two approaches in (a) the normal rat brain when the rats were submitted to hypoxemia; (b) animals implanted with four tumour types differentiated by their oxygenation. Rats were submitted to normoxic and hypoxemic conditions. For the brain tumour experiments, U87-MG, U251-MG, 9L and C6 glioma cells were orthotopically inoculated in rats. For both experiments, StO2-MRI and [18F]-FMISO PET were performed sequentially. Under hypoxemia conditions, StO2-MRI revealed a decrease in oxygen saturation in the brain. Nonetheless, [18F]-FMISO PET, pimonidazole immunohistochemistry and molecular biology were insensitive to hypoxia. Within the context of tumours, StO2-MRI was able to detect hypoxia in the hypoxic models, mimicking [18F]-FMISO PET with high sensitivity/specificity. Altogether, our data clearly support that, in brain pathologies, StO2-MRI could be a robust and specific imaging biomarker to assess hypoxia. [ABSTRACT FROM AUTHOR]

Purpose: The primary objective of this study was to compare the ability of PET and MRI biomarkers to predict treatment efficacy in a preclinical model of recurrent glioblastoma multiforme. Methods: MRI (anatomical, diffusion, vasculature and oxygenation) and PET ([F]FDG and [F]FLT) parameters were obtained 3 days after the end of treatment and compared with late tumour growth and survival. Results: Early after tumour recurrence, no effect of treatment with temozolomide combined with bevacizumab was observed on tumour volume as assessed by T2-W MRI. At later times, the treatment decreased tumour volume and increased survival. Interestingly, at the earlier time, temozolomide + bevacizumab decreased [F]FLT uptake, cerebral blood volume and oedema. [F]FLT uptake, oedema and cerebral blood volume were correlated with overall survival but [F]FLT uptake had the highest specificity and sensitivity for the early prediction of treatment efficacy. Conclusion: The present investigation in a preclinical model of glioblastoma recurrence underscores the importance of multimodal imaging in the assessment of oedema, tumour vascular status and cell proliferation. Finally, [F]FLT holds the greatest promise for the early assessment of treatment efficacy. These findings may translate clinically in that individualized treatment for recurrent glioma could be prescribed for patients selected after PET/MRI examinations. [ABSTRACT FROM AUTHOR]

Simple Summary: Due to the central role of magnetic resonance Imaging (MRI) in the management of patients with cancer, waiting lists exceed clinically relevant delays. For this reason, many research groups and MRI manufacturers develop algorithms as resampling and denoising models to allow faster acquisition time without deterioration in image quality. Whereas these algorithms are available in all new MRI, it is not clear how they will impact image features as well as the validity of statistical model of radiomics which use deep images characteristics to predict treatment outcome. The aim of this study was to develop resampling and denoising deep learning (DL) models and evaluate their impact on radiomics from post-Gd-T1w-MRI brain images with brain metastases. We show that resampling and denoising DL models reconstruct low resolution and noised MRI images acquired quickly into high quality images. While fast acquisition loses most of the radiomic-features and invalidates predictive radiomic models, DL models restore these parameters. Background: Magnetic resonance imaging (MRI) is predominant in the therapeutic management of cancer patients, unfortunately, patients have to wait a long time to get an appointment for examination. Therefore, new MRI devices include deep-learning (DL) solutions to save acquisition time. However, the impact of these algorithms on intensity and texture parameters has been poorly studied. The aim of this study was to evaluate the impact of resampling and denoising DL models on radiomics. Methods: Resampling and denoising DL model was developed on 14,243 T1 brain images from 1.5T-MRI. Radiomics were extracted from 40 brain metastases from 11 patients (2049 images). A total of 104 texture features of DL images were compared to original images with paired t-test, Pearson correlation and concordance-correlation-coefficient (CCC). Results: When two times shorter image acquisition shows strong disparities with the originals concerning the radiomics, with significant differences and loss of correlation of 79.81% and 48.08%, respectively. Interestingly, DL models restore textures with 46.15% of unstable parameters and 25.96% of low CCC and without difference for the first-order intensity parameters. Conclusions: Resampling and denoising DL models reconstruct low resolution and noised MRI images acquired quickly into high quality images. While fast MRI acquisition loses most of the radiomic features, DL models restore these parameters. [ABSTRACT FROM AUTHOR]