Microbeam Radiation Therapy Opens a Several Days' Vessel Permeability Window for Small Molecules in Brain Tumor Vessels.

PURPOSE: Synchrotron microbeam radiation therapy (MRT), based on an inhomogeneous geometric and microscopic irradiation pattern of the tissues with high-dose and high-dose-rate x-rays, enhances the permeability of brain tumor vessels. This study attempted to determine the time and size range of the permeability window induced by MRT in the blood-brain (tumor) barrier. METHODS AND MATERIALS: Rats-bearing 9L gliomas were exposed to MRT, either unidirectional (tumor dose, 406 Gy) or bidirectional (crossfired) (2 × 203 Gy). We measured vessel permeability to molecules of 3 sizes (Gd-DOTA, Dotarem, 0.56 kDa; gadolinium-labeled albumin, ∼74 kDa; and gadolinium-labeled IgG, 160 kDa) by daily in vivo magnetic resonance imaging, from 1 day before to 10 days after irradiation. RESULTS: An equivalent tumor dose of bidirectional MRT delivered from 2 orthogonal directions increased tumor vessel permeability for the smallest molecule tested more effectively than unidirectional MRT. Bidirectional MRT also affected the permeability of normal contralateral vessels to a different extent than unidirectional MRT. Conversely, bidirectional MRT did not modify the permeability of normal or tumor vessels for both larger molecules (74 and 160 kDa). CONCLUSIONS: High-dose bidirectional (cross-fired) MRT induced a significant increase in tumor vessel permeability for small molecules between the first and the seventh day after irradiation, whereas permeability of vessels in normal brain tissue remained stable. Such a permeability window could facilitate an efficient and safe delivery of intravenous small molecules (≤0.56 kDa) to tumoral tissues. A permeability window was not achieved by molecules larger than gado-grafted albumin (74 kDa). Vascular permeability for molecules between these 2 sizes has not been determined.

Prediction of therapeutic intensity level from automatic multiclass segmentation of traumatic brain injury lesions on CT-scans.

The prediction of the therapeutic intensity level (TIL) for severe traumatic brain injury (TBI) patients at the early phase of intensive care unit (ICU) remains challenging. Computed tomography images are still manually quantified and then underexploited. In this study, we develop an artificial intelligence-based tool to segment brain lesions on admission CT-scan and predict TIL within the first week in the ICU. A cohort of 29 head injured patients (87 CT-scans; Dataset1) was used to localize (using a structural atlas), segment (manually or automatically with or without transfer learning) 4 or 7 types of lesions and use these metrics to train classifiers, evaluated with AUC on a nested cross-validation, to predict requirements for TIL sum of 11 points or more during the 8 first days in ICU. The validation of the performances of both segmentation and classification tasks was done with Dice and accuracy scores on a sub-dataset of Dataset1 (internal validation) and an external dataset of 12 TBI patients (12 CT-scans; Dataset2). Automatic 4-class segmentation (without transfer learning) was not able to correctly predict the apparition of a day of extreme TIL (AUC = 60 ± 23%). In contrast, manual quantification of volumes of 7 lesions and their spatial location provided a significantly better prediction power (AUC = 89 ± 17%). Transfer learning significantly improved the automatic 4-class segmentation (DICE scores 0.63 vs 0.34) and trained more efficiently a 7-class convolutional neural network (DICE = 0.64). Both validations showed that segmentations based on transfer learning were able to predict extreme TIL with better or equivalent accuracy (83%) as those made with manual segmentations. Our automatic characterization (volume, type and spatial location) of initial brain lesions observed on CT-scan, publicly available on a dedicated computing platform, could predict requirements for high TIL during the first 8 days after severe TBI. Transfer learning strategies may improve the accuracy of CNN-based segmentation models.Trial registrations Radiomic-TBI cohort; NCT04058379, first posted: 15 august 2019; Radioxy-TC cohort; Health Data Hub index F20220207212747, first posted: 7 February 2022.

Radiomics-Based Detection of Radionecrosis Using Harmonized Multiparametric MRI.

In this study, a radiomics analysis was conducted to provide insights into the differentiation of radionecrosis and tumor progression in multiparametric MRI in the context of a multicentric clinical trial. First, the sensitivity of radiomic features to the unwanted variability caused by different protocol settings was assessed for each modality. Then, the ability of image normalization and ComBat-based harmonization to reduce the scanner-related variability was evaluated. Finally, the performances of several radiomic models dedicated to the classification of MRI examinations were measured. Our results showed that using radiomic models trained on harmonized data achieved better predictive performance for the investigated clinical outcome (balanced accuracy of 0.61 with the model based on raw data and 0.72 with ComBat harmonization). A comparison of several models based on information extracted from different MR modalities showed that the best classification accuracy was achieved with a model based on MR perfusion features in conjunction with clinical observation (balanced accuracy of 0.76 using LASSO feature selection and a Random Forest classifier). Although multimodality did not provide additional benefit in predictive power, the model based on T1-weighted MRI before injection provided an accuracy close to the performance achieved with perfusion.

Contribution of CT-Scan Analysis by Artificial Intelligence to the Clinical Care of TBI Patients.

The gold standard to diagnose intracerebral lesions after traumatic brain injury (TBI) is computed tomography (CT) scan, and due to its accessibility and improved quality of images, the global burden of CT scan for TBI patients is increasing. The recent developments of automated determination of traumatic brain lesions and medical-decision process using artificial intelligence (AI) represent opportunities to help clinicians in screening more patients, identifying the nature and volume of lesions and estimating the patient outcome. This short review will summarize what is ongoing with the use of AI and CT scan for patients with TBI.

Bayesian Inverse Regression for Vascular Magnetic Resonance Fingerprinting.

Standard parameter estimation from vascular magnetic resonance fingerprinting (MRF) data is based on matching the MRF signals to their best counterparts in a grid of coupled simulated signals and parameters, referred to as a dictionary. To reach a good accuracy, the matching requires an informative dictionary whose cost, in terms of design, storage and exploration, is rapidly prohibitive for even moderate numbers of parameters. In this work, we propose an alternative dictionary-based statistical learning (DB-SL) approach made of three steps: 1) a quasi-random sampling strategy to produce efficiently an informative dictionary, 2) an inverse statistical regression model to learn from the dictionary a correspondence between fingerprints and parameters, and 3) the use of this mapping to provide both parameter estimates and their confidence indices. The proposed DB-SL approach is compared to both the standard dictionary-based matching (DBM) method and to a dictionary-based deep learning (DB-DL) method. Performance is illustrated first on synthetic signals including scalable and standard MRF signals with spatial undersampling noise. Then, vascular MRF signals are considered both through simulations and real data acquired in tumor bearing rats. Overall, the two learning methods yield more accurate parameter estimates than matching and to a range not limited to the dictionary boundaries. DB-SL in particular resists to higher noise levels and provides in addition confidence indices on the estimates at no additional cost. DB-SL appears as a promising method to reduce simulation needs and computational requirements, while modeling sources of uncertainty and providing both accurate and interpretable results.

In vivo characterization of physiological and metabolic changes related to isocitrate dehydrogenase 1 mutation expcression by multiparametric MRI and MRS in a rat model with orthotopically grafted human-derived glioblastoma cell lines.

The physiological mechanism induced by the isocitrate dehydrogenase 1 (IDH1) mutation, associated with better treatment response in gliomas, remains unknown. The aim of this preclinical study was to characterize the IDH1 mutation through in vivo multiparametric MRI and MRS. Multiparametric MRI, including the measurement of blood flow, vascularity, oxygenation, permeability, and in vivo MRS, was performed on a 4.7 T animal MRI system in rat brains grafted with human-derived glioblastoma U87 cell lines expressing or not the IDH1 mutation by the CRISPR/Cas9 method, and secondarily characterized with additional ex vivo HR-MAS and histological analyses. In univariate analyses, compared with IDH1-, IDH1+ tumors exhibited higher vascular density (p < 0.01) and better perfusion (p = 0.02 for cerebral blood flow), but lower vessel permeability (p < 0.01 for time to peak (TTP), p = 0.04 for contrast enhancement) and decreased T1 map values (p = 0.02). Using linear discriminant analysis, vascular density and TTP values were found to be independent MRI parameters for characterizing the IDH1 mutation (p < 0.01). In vivo MRS and ex vivo HR-MAS analysis showed lower metabolites of tumor aggressiveness for IDH1+ tumors (p < 0.01). Overall, the IDH1 mutation exhibited a higher vascularity on MRI, a lower permeability, and a less aggressive metabolic profile. These MRI features may prove helpful to better pinpoint the physiological mechanisms induced by this mutation.

Calcified cartilage revealed in whole joint by X-ray phase contrast imaging.

Objective: X-ray Phase Contrast Imaging (PCI) is an emerging modality that will be in the next few years available in a wider range of preclinical set-ups. In this study, we compare this imaging technique with conventional preclinical modalities in an osteoarthritis mouse model. Method: Phase contrast technique was performed on 6 post-mortem, monoiodoacetate-induced osteoarthritis knees and 6 control knees. The mice knees were then imaged using magnetic resonance imaging and conventional micro computed tomography. Examples of imaging surrogate markers are reported: local distances within the articular space, cartilage surface roughness, calcified cartilage thickness, number, volume and locations of osteophytes. Results: Thanks to PCI, we can show in 3D calcified cartilage without contrast agent by a non-invasive technique. The phase contrast images reveal more details than conventional imaging techniques, especially at smaller scales, with for instance a higher number of micro-calcifications detected (57, 314 and 329 for MRI, conventional micro-CT and phase contrast imaging respectively). Calcified cartilage thickness was measured with a significant difference (p â€‹< â€‹0.01) between the control (23.4 â€‹± â€‹17.2 â€‹µm) and the osteoarthritis induced animal (46.9 â€‹± â€‹19.0 â€‹µm). Conclusions: X-ray phase contrast imaging outperforms the conventional imaging modalities for assessing the different tissue types (soft and hard). This new imaging modality seems to bring new relevant surrogate markers for following-up small animal models even for low-grade osteoarthritis.

Hypertonic Sodium Lactate to Alleviate Functional Deficits Following Diffuse Traumatic Brain Injury: An Osmotic or a Lactate-Related Effect?

BACKGROUND: There has been growing interest in the use of hypertonic sodium lactate (HSL) solution following traumatic brain injury (TBI) in humans. However, little is known about the effects of HSL on functional deficits with respect to the hyperosmotic nature of HSL. METHODS: We have compared the effects of HSL solution and isotonic saline solution using sensorimotor and cognitive tests for 14 days post-trauma in animals. Thirty minutes after trauma (impact-acceleration model), anesthetized rats were randomly allocated to receive a 2-h infusion of isotonic saline solution (TBI-saline group) or HSL (TBI-HSL group) (n = 10 rats per group). In another series of experiments using a similar protocol, the effects of equiosmolar doses of HSL and hypertonic saline solution (HSS) were compared in TBI rats (n = 10 rats per group). Blood lactate and ion concentrations were measured during the 2-h infusions. RESULTS: Compared to the TBI-saline group, the TBI-HSL group had a reduced latency to complete the adhesive removal test: 6 s (5-9) (median [25-75th centiles]) versus 13 s (8-17) on day 7, and 5 s (5-9) versus 11 s (8-26) on day 14 (P < 0.05), respectively, and a shorter delay to complete the radial arm maze test on day 7: 99 s (73-134) versus 176 s (127-300), respectively (P < 0.05). However, no differences were found between the TBI-HSL and TBI-HSS groups in neurocognitive tests performance. Compared to the TBI-saline group, the HSL and HSS groups had higher serum osmolality: 318 mOsm/Kg (315-321) and 315 mOsm/Kg (313-316) versus 307 mOsm/Kg (305-309), respectively (P < 0.05), and the HSL group had a higher serum lactate concentration: 6.4 mmol/L (5.3-7.2) versus 1.5 mmol/L (1.1-1.9) and 1.6 mmol/L (1.5-1.7), respectively (P < 0.05). CONCLUSIONS: These results indicate that improvements in cognitive and sensorimotor tests with HSL infusion post-TBI could be related to elevation of serum osmolality, not to exogenous administration of lactate.

Parametric Response Mapping of FLAIR MRI Provides an Early Indication of Progression Risk in Glioblastoma.

RATIONALE AND OBJECTIVES: Glioblastoma image evaluation utilizes Magnetic Resonance Imaging contrast-enhanced, T1-weighted, and noncontrast T2-weighted fluid-attenuated inversion recovery (FLAIR) acquisitions. Disease progression assessment relies on changes in tumor diameter, which correlate poorly with survival. To improve treatment monitoring in glioblastoma, we investigated serial voxel-wise comparison of anatomically-aligned FLAIR signal as an early predictor of GBM progression. MATERIALS AND METHODS: We analyzed longitudinal normalized FLAIR images (rFLAIR) from 52 subjects using voxel-wise Parametric Response Mapping (PRM) to monitor volume fractions of increased (PRMrFLAIR+), decreased (PRMrFLAIR-), or unchanged (PRMrFLAIR0) rFLAIR intensity. We determined response by rFLAIR between pretreatment and 10 weeks posttreatment. Risk of disease progression in a subset of subjects (N = 26) with stable disease or partial response as defined by Response Assessment in Neuro-Oncology (RANO) criteria was assessed by PRMrFLAIR between weeks 10 and 20 and continuously until the PRMrFLAIR+ exceeded a defined threshold. RANO defined criteria were compared with PRM-derived outcomes for tumor progression detection. RESULTS: Patient stratification for progression-free survival (PFS) and overall survival (OS) was achieved at week 10 using RANO criteria (PFS: p <0.0001; OS: p <0.0001), relative change in FLAIR-hyperintense volume (PFS: p = 0.0011; OS: p <0.0001), and PRMrFLAIR+ (PFS: p <0.01; OS: p <0.001). PRMrFLAIR+ also stratified responding patients' progression between weeks 10 and 20 (PFS: p <0.05; OS: p = 0.01) while changes in FLAIR-volume measurements were not predictive. As a continuous evaluation, PRMrFLAIR+ exceeding 10% stratified patients for PFA after 5.6 months (p<0.0001), while RANO criteria did not stratify patients until 15.4 months (p <0.0001). CONCLUSION: PRMrFLAIR may provide an early biomarker of disease progression in glioblastoma.

MP3: Medical Software for Processing Multi-Parametric Images Pipelines.

This article presents an open source software able to convert, display, and process medical images. It differentiates itself from the existing software by its ability to design complex processing pipelines and to wisely execute them on a large databases. An MP3 pipeline can contain unlimited homemade or ready-made processes and can be carried out with a parallel execution system. As a viewer, MP3 allows display of up to four images together and to draw Regions Of Interest (ROI). Two applications showing the strengths of the software are presented as examples: a preclinical study involving Magnetic Resonance Imaging (MRI) data and a clinical one involving Computed Tomography (CT) images. MP3 is downloadable at https://github.com/nifm-gin/MP3.

Targeting brain metastases with ultrasmall theranostic nanoparticles, a first-in-human trial from an MRI perspective.

The use of radiosensitizing nanoparticles with both imaging and therapeutic properties on the same nano-object is regarded as a major and promising approach to improve the effectiveness of radiotherapy. Here, we report the MRI findings of a phase 1 clinical trial with a single intravenous administration of Gd-based AGuIX nanoparticles, conducted in 15 patients with four types of brain metastases (melanoma, lung, colon, and breast). The nanoparticles were found to accumulate and to increase image contrast in all types of brain metastases with MRI enhancements equivalent to that of a clinically used contrast agent. The presence of nanoparticles in metastases was monitored and quantified with MRI and was noticed up to 1 week after their administration. To take advantage of the radiosensitizing property of the nanoparticles, patients underwent radiotherapy sessions following their administration. This protocol has been extended to a multicentric phase 2 clinical trial including 100 patients.

Locomotion and eating behavior changes in Yucatan minipigs after unilateral radio-induced ablation of the caudate nucleus.

The functional roles of the Caudate nucleus (Cd) are well known. Selective Cd lesions can be found in neurological disorders. However, little is known about the dynamics of the behavioral changes during progressive Cd ablation. Current stereotactic radiosurgery technologies allow the progressive ablation of a brain region with limited adverse effects in surrounding normal tissues. This could be of high interest for the study of the modified behavioral functions in relation with the degree of impairment of the brain structures. Using hypofractionated stereotactic radiotherapy combined with synchrotron microbeam radiation, we investigated, during one year after irradiation, the effects of unilateral radio-ablation of the right Cd on the behavior of Yucatan minipigs. The right Cd was irradiated to a minimal dose of 35.5 Gy delivered in three fractions. MRI-based morphological brain integrity and behavioral functions, i.e. locomotion, motivation/hedonism were assessed. We detected a progressive radio-necrosis leading to a quasi-total ablation one year after irradiation, with an additional alteration of surrounding areas. Transitory changes in the motivation/hedonism were firstly detected, then on locomotion, suggesting the influence of different compensatory mechanisms depending on the functions related to Cd and possibly some surrounding areas. We concluded that early behavioral changes related to eating functions are relevant markers for the early detection of ongoing lesions occurring in Cd-related neurological disorders.

Fully Automatic Lesion Localization and Characterization: Application to Brain Tumors Using Multiparametric Quantitative MRI Data.

When analyzing brain tumors, two tasks are intrinsically linked, spatial localization, and physiological characterization of the lesioned tissues. Automated data-driven solutions exist, based on image segmentation techniques or physiological parameters analysis, but for each task separately, the other being performedmanually or with user tuning operations. In this paper, the availability of quantitative magnetic resonance (MR) parameters is combined with advancedmultivariate statistical tools to design a fully automated method that jointly performs both localization and characterization. Non trivial interactions between relevant physiologicalparameters are capturedthanks to recent generalized Student distributions that provide a larger variety of distributional shapes compared to the more standard Gaussian distributions. Probabilisticmixtures of the former distributions are then consideredto account for the different tissue types and potential heterogeneity of lesions. Discriminative multivariate features are extracted from this mixture modeling and turned into individual lesion signatures. The signatures are subsequently pooled together to build a statistical fingerprintmodel of the different lesion types that captures lesion characteristics while accounting for inter-subject variability. The potential of this generic procedure is demonstrated on a data set of 53 rats, with 36 rats bearing 4 different brain tumors, for which 5 quantitative MR parameters were acquired.

Cluster versus ROI analysis to assess combined antiangiogenic therapy and radiotherapy in the F98 rat-glioma model.

For glioblastoma (GBM), current therapeutic approaches focus on the combination of several therapies, each of them individually approved for GBM or other tumor types. Many efforts are made to decipher the best sequence of treatments that would ultimately promote the most efficient tumor response. There is therefore a strong interest in developing new clinical in vivo imaging procedures that can rapidly detect treatment efficacy and allow individual modulation of the treatment. In this preclinical study, we propose to evaluate tumor tissue changes under combined therapies, tumor vascular normalization under antiangiogenic treatment followed by radiotherapy, using a voxel-based clustering approach. This approach was applied to a rat model of glioma (F98). Six MRI parameters were mapped: apparent diffusion coefficient, vessel wall permeability, cerebral blood volume fraction, cerebral blood flow, tissue oxygen saturation and vessel size index. We compared the classical region of interest (ROI)-based analysis with a cluster-based analysis. Five clusters, defined by their MRI features, were sufficient to characterize tumor progression and tumor changes during treatments. These results suggest that the cluster-based analysis was as efficient as the ROI-based analysis to assess tumor physiological changes during treatment, but also gave additional information regarding the voxels impacted by treatments and their localization within the tumor. Overall, cluster-based analysis appears to be a powerful tool for subtle monitoring of tumor changes during combined therapies.

Evaluation of Parametric Response Mapping to Assess Therapeutic Response to Human Mesenchymal Stem Cells after Experimental Stroke.

Stroke is the leading cause of disability in adults. After the very narrow time frame during which treatment by thrombolysis and mechanical thrombectomy is possible, cell therapy has huge potential for enhancing stroke recovery. Accurate analysis of the response to new therapy using imaging biomarkers is needed to assess therapeutic efficacy. The aim of this study was to compare 2 analysis techniques: the parametric response map (PRM), a voxel-based technique, and the standard whole-lesion approach. These 2 analyses were performed on data collected at 4 time points in a transient middle cerebral artery occlusion (MCAo) model, which was treated with human mesenchymal stem cells (hMSCs). The apparent diffusion coefficient (ADC), cerebral blood volume (CBV), and vessel size index (VSI) were mapped using magnetic resonance imaging (MRI). Two groups of rats received an intravenous injection of either 1 mL phosphate-buffered saline (PBS)-glutamine (MCAo-PBS, n = 10) or 3 million hMSCs (MCAo-hMSC, n = 10). One sham group was given PBS-glutamine (sham, n = 12). Each MRI parameter was analyzed by both the PRM and the whole-lesion approach. At day 9, 1 d after grafting, PRM revealed that hMSCs had reduced the fraction of decreased ADC (PRMADC-: MCAo-PBS 6.7% ± 1.7% vs. MCAo-hMSC 3.3% ± 2.4%), abolished the fraction of increased CBV (PRMCBV+: MCAo-PBS 16.1% ± 3.7% vs. MCAo-hMSC 6.4% ± 2.6%), and delayed the fraction of increased VSI (PRMVSI+: MCAo-PBS 17.5% ± 6.3% vs. MCAo-hMSC 5.4% ± 2.6%). The whole-lesion approach was, however, insensitive to these early modifications. PRM thus appears to be a promising technique for the detection of early brain changes following treatments such as cell therapy.

Permeability of Brain Tumor Vessels Induced by Uniform or Spatially Microfractionated Synchrotron Radiation Therapies.

PURPOSE: To compare the blood-brain barrier permeability changes induced by synchrotron microbeam radiation therapy (MRT, which relies on spatial fractionation of the incident x-ray beam into parallel micron-wide beams) with changes induced by a spatially uniform synchrotron x-ray radiation therapy. METHODS AND MATERIALS: Male rats bearing malignant intracranial F98 gliomas were randomized into 3 groups: untreated, exposed to MRT (peak and valley dose: 241 and 10.5 Gy, respectively), or exposed to broad beam irradiation (BB) delivered at comparable doses (ie, equivalent to MRT valley dose); both applied by 2 arrays, intersecting orthogonally the tumor region. Vessel permeability was monitored in vivo by magnetic resonance imaging 1 day before (T-1) and 1, 2, 7, and 14 days after treatment start. To determine whether physiologic parameters influence vascular permeability, we evaluated vessel integrity in the tumor area with different values for cerebral blood flow, blood volume, edema, and tissue oxygenation. RESULTS: Microbeam radiation therapy does not modify the vascular permeability of normal brain tissue. Microbeam radiation therapy-induced increase of tumor vascular permeability was detectable from T2 with a maximum at T7 after exposure, whereas BB enhanced vessel permeability only at T7. At this stage MRT was more efficient at increasing tumor vessel permeability (BB vs untreated: +19.1%; P=.0467; MRT vs untreated: +44.8%; P<.0001), and its effects lasted until T14 (MRT vs BB, +22.6%; P=.0199). We also showed that MRT was more efficient at targeting highly oxygenated (high blood volume and flow) and more proliferative parts of the tumor than BB. CONCLUSIONS: Microbeam radiation therapy-induced increased tumor vascular permeability is: (1) significantly greater; (2) earlier and more prolonged than that induced by BB irradiation, especially in highly proliferative tumor areas; and (3) targets all tumor areas discriminated by physiologic characteristics, including those not damaged by homogeneous irradiation.

Multiparametric magnetic resonance imaging including oxygenation mapping of experimental ischaemic stroke.

Recent advances in MRI methodology, such as microvascular and brain oxygenation (StO2) imaging, may prove useful in obtaining information about the severity of the acute stroke. We assessed the potential of StO2 to detect the ischaemic core in the acute phase compared to apparent diffusion coefficient and to predict the final necrosis. Sprague-Dawley rats (n = 38) were imaged during acute stroke (D0) and 21 days after (D21). A multiparametric MRI protocol was performed at 4.7T to characterize brain damage within three region of interest: 'LesionD0' (diffusion), 'Mismatch' representing penumbra (perfusion/diffusion) and 'Hypoxia' (voxels < 40% of StO2 within the region of interest LesionD0). Voxel-based analysis of stroke revealed heterogeneity of the region of interest LesionD0, which included voxels with different degrees of oxygenation decrease. This finding was supported by a dramatic decrease of vascular and perfusion parameters within the region of interest hypoxia. This zone presented the lowest values of almost all parameters analysed, indicating a higher severity. Our study demonstrates the potential of StO2 magnetic resonance imaging to more accurately detect the ischaemic core without the inclusion of any reversible ischaemic damage. Our follow-up study indicates that apparent diffusion coefficient imaging overestimated the final necrosis while StO2 imaging did not.

Evaluation of Concurrent Radiation, Temozolomide and ABT-888 Treatment Followed by Maintenance Therapy with Temozolomide and ABT-888 in a Genetically Engineered Glioblastoma Mouse Model.

Despite the use of ionizing radiation (IR) and temozolomide (TMZ), outcome for glioblastoma (GBM) patients remains dismal. Poly (ADP-ribose) polymerase (PARP) is important in repair pathways for IR-induced DNA damage and TMZ-induced alkylation at N7-methylguanine and N3-methyldenine. However, optimized protocols for administration of PARP inhibitors have not been delineated. In this study, the PARP inhibitor ABT-888 was evaluated in combination with and compared to current standard-of-care in a genetically engineered mouse GBM model. Results demonstrated that concomitant TMZ/IR/ABT-888 with adjuvant TMZ/ABT-888 was more effective in inducing apoptosis and reducing proliferation with significant tumor growth delay and improved overall survival over concomitant TMZ/IR with adjuvant TMZ. Diffusion-weighted MRI, an early translatable response biomarker detected changes in tumors reflecting response at 1 day post TMZ/IR/ABT-888 treatment. This study provides strong scientific rationale for the development of an optimized dosing regimen for a PARP inhibitor with TMZ/IR for upfront treatment of GBM.

Development of a Multiparametric Voxel-Based Magnetic Resonance Imaging Biomarker for Early Cancer Therapeutic Response Assessment.

Quantitative magnetic resonance imaging (MRI)-based biomarkers, which capture physiological and functional tumor processes, were evaluated as imaging surrogates of early tumor response following chemoradiotherapy in glioma patients. A multiparametric extension of a voxel-based analysis, referred as the parametric response map (PRM), was applied to quantitative MRI maps to test the predictive potential of this metric for detecting response. Fifty-six subjects with newly diagnosed high-grade gliomas treated with radiation and concurrent temozolomide were enrolled in a single-site prospective institutional review board-approved MRI study. Apparent diffusion coefficient (ADC) and relative cerebral blood volume (rCBV) maps were acquired before therapy and 3 weeks after therapy was initiated. Multiparametric PRM (mPRM) was applied to both physiological MRI maps and evaluated as an imaging biomarker of patient survival. For comparison, single-biomarker PRMs were also evaluated in this study. The simultaneous analysis of ADC and rCBV by the mPRM approach was found to improve the predictive potential for patient survival over single PRM measures. With an array of quantitative imaging parameters being evaluated as biomarkers of therapeutic response, mPRM shows promise as a new methodology for consolidating physiologically distinct imaging parameters into a single interpretable and quantitative metric.

Multiparametric MRI as an early biomarker of individual therapy effects during concomitant treatment of brain tumours.

The aim of this study was to determine the ability of multiparametric MRI to identify the early effects of individual treatment, during combined chemo-radiotherapy on brain tumours. Eighty male rats bearing 9L gliosarcomas were randomized into four groups: untreated, anti-angiogenic therapy (SORA group), microbeam radiation therapy (MRT group) and both treatments (MRT+SORA group). Multiparametric MRI (tumour volume, diffusion-weighted MR imaging (ADC), blood volume fraction (BVf), microvessel index (VSI), vessel wall integrity (AUC(P846)) and tissue oxygen saturation (StO2)) was performed 1 day before and 2, 5 and 8 days after treatment initiation. Unpaired t-tests and one-way ANOVA were used for statistical analyses. Each MR parameter measured in our protocol was revealed to be sensitive to tumour changes induced by any of the therapies used (individually or combined). When compared with untreated tumours, SORA induced a decrease in BVf, VSI, StO2 and AUC(P846), MRT generated an increase in ADC and AUC(P846) and combined therapies yielded mixed effects: an increase in ADC and AUC(P846) and a decrease in BVf, StO2 and AUC(P846). MRT and MRT+SORA significantly slowed tumour growth. Despite these two groups presenting with similar tumour sizes, the information yielded from MR multiparameter assessment indicated that, when used concomitantly, each therapy induced distinguishable and appreciable physiological changes in the tumour. Our results suggest that multiparametric MRI can monitor the effects of individual treatments, used concomitantly, on brain tumours. Such monitoring would be useful for the detection of tumour resistance to drug/radiotherapy in patients undergoing concomitant therapies.