A convolutional neural network to filter artifacts in spectroscopic MRI

Purpose Proton MRSI is a noninvasive modality capable of generating volumetric maps of in vivo tissue metabolism without the need for ionizing radiation or injected contrast agent. Magnetic resonance spectroscopic imaging has been shown to be a viable imaging modality for studying several neuropathologies. However, a key hurdle in the routine clinical adoption of MRSI is the presence of spectral artifacts that can arise from a number of sources, possibly leading to false information. Methods A deep learning model was developed that was capable of identifying and filtering out poor quality spectra. The core of the model used a tiled convolutional neural network that analyzed frequency‐domain spectra to detect artifacts. Results When compared with a panel of MRS experts, our convolutional neural network achieved high sensitivity and specificity with an area under the curve of 0.95. A visualization scheme was implemented to better understand how the convolutional neural network made its judgement on single‐voxel or multivoxel MRSI, and the convolutional neural network was embedded into a pipeline capable of producing whole‐brain spectroscopic MRI volumes in real time. Conclusion The fully automated method for assessment of spectral quality provides a valuable tool to support clinical MRSI or spectroscopic MRI studies for use in fields such as adaptive radiation therapy planning

The Longitudinal Imaging Tracker (BrICS-LIT):A Cloud Platform for Monitoring Treatment Response in Glioblastoma Patients

Glioblastoma is a common and aggressive form of brain cancer affecting up to 20,000 new patients in the US annually. Despite rigorous therapies, current median survival is only 15–20 months. Patients who complete initial treatment undergo follow-up imaging at routine intervals to assess for tumor recurrence. Imaging is a central part of brain tumor management, but MRI findings in patients with brain tumor can be challenging to interpret and are further confounded by interpretation variability. Disease-specific structured reporting attempts to reduce variability in imaging results by implementing well-defined imaging criteria and standardized language. The Brain Tumor Reporting and Data System (BT-RADS) is one such framework streamlined for clinical workflows and includes quantitative criteria for more objective evaluation of follow-up imaging. To facilitate accurate and objective monitoring of patients during the follow-up period, we developed a cloud platform, the Brain Imaging Collaborative Suite's Longitudinal Imaging Tracker (BrICS-LIT). BrICS-LIT uses semiautomated tumor segmentation algorithms of both T2-weighted FLAIR and contrast-enhanced T1-weighted MRI to assist clinicians in quantitative assessment of brain tumors. The LIT platform can ultimately guide clinical decision-making for patients with glioblastoma by providing quantitative metrics for BT-RADS scoring. Further, this platform has the potential to increase objectivity when measuring efficacy of novel therapies for patients with brain tumor during their follow-up. Therefore, LIT will be used to track patients in a dose-escalated clinical trial, where spectroscopic MRI has been used to guide radiation therapy (Clinicaltrials.gov NCT03137888), and compare patients to a control group that received standard of care

The Longitudinal Imaging Tracker (BrICS-LIT):A Cloud Platform for Monitoring Treatment Response in Glioblastoma Patients

Glioblastoma is a common and aggressive form of brain cancer affecting up to 20,000 new patients in the US annually. Despite rigorous therapies, current median survival is only 15–20 months. Patients who complete initial treatment undergo follow-up imaging at routine intervals to assess for tumor recurrence. Imaging is a central part of brain tumor management, but MRI findings in patients with brain tumor can be challenging to interpret and are further confounded by interpretation variability. Disease-specific structured reporting attempts to reduce variability in imaging results by implementing well-defined imaging criteria and standardized language. The Brain Tumor Reporting and Data System (BT-RADS) is one such framework streamlined for clinical workflows and includes quantitative criteria for more objective evaluation of follow-up imaging. To facilitate accurate and objective monitoring of patients during the follow-up period, we developed a cloud platform, the Brain Imaging Collaborative Suite\u27s Longitudinal Imaging Tracker (BrICS-LIT). BrICS-LIT uses semiautomated tumor segmentation algorithms of both T2-weighted FLAIR and contrast-enhanced T1-weighted MRI to assist clinicians in quantitative assessment of brain tumors. The LIT platform can ultimately guide clinical decision-making for patients with glioblastoma by providing quantitative metrics for BT-RADS scoring. Further, this platform has the potential to increase objectivity when measuring efficacy of novel therapies for patients with brain tumor during their follow-up. Therefore, LIT will be used to track patients in a dose-escalated clinical trial, where spectroscopic MRI has been used to guide radiation therapy (Clinicaltrials.gov NCT03137888), and compare patients to a control group that received standard of care

A Systematic Pipeline for the Objective Comparison of Whole-Brain Spectroscopic MRI with Histology in Biopsy Specimens from Grade 3 Glioma

The diagnosis, prognosis, and management of patients with gliomas are largely dictated by the pathological analysis of tissue biopsied from a selected region within the lesion. However, the heterogeneous and infiltrative nature of gliomas make it difficult to identify the optimal region for biopsy with conventional magnetic resonance imaging (MRI). This is particularly true for low-grade gliomas, which are often nonenhancing tumors. To improve the management of patients with such tumors, neuro-oncology requires an imaging modality that can specifically identify a tumor\u27s most anaplastic/aggressive region(s) for biopsy targeting. The addition of metabolic mapping using spectroscopic MRI (sMRI) to supplement conventional MRI could improve biopsy targeting and, ultimately, diagnostic accuracy. Here, we describe a pipeline for the integration of state-of-the-art, high-resolution, whole-brain 3-dimensional sMRI maps into a stereotactic neuronavigation system for guiding biopsies in gliomas with nonenhancing components. We also outline a machine-learning method for automated histological analysis that generates normalized, quantitative metrics describing tumor infiltration in immunohistochemically stained tissue specimens. As a proof of concept, we describe the combination of these 2 techniques in a small cohort of patients with grade 3 glioma. With this work, we aim to present a systematic pipeline to stimulate histopathological image validation of advanced MRI techniques, such as sMRI

A multisite clinical trial of spectroscopic MRI-guided radiation dose escalation for newly-diagnosed glioblastomas

2018 Background: Glioblastoma (GBM) is the most common adult primary malignant brain tumor. These pts have poor outcomes [median overall survival (OS) ̃ 16 months] despite radiation therapy (RT) to 60 Gy and temozolomide (TMZ). Magnetic resonance spectroscopy (MRS) measures levels of specific metabolites in the brain including choline (Cho) and N-acetyl aspartate (NAA). Previously, we found that high Cho/NAA ratios can aid in localizing regions of brain at high risk for GBM recurrence that may not be appreciated on standard contrast-enhanced (CE) MRI. Based on this finding, we conducted a clinical trial to assess the feasibility and safety of using an advanced volumetric MRS technique termed spectroscopic MRI (sMRI) to guide RT dose escalation for newly-diagnosed GBMs. Methods: Our clinical trial (NCT03137888) funded by the NCI (RO1CA214557) enrolled pts at 3 institutions (Emory U, U Miami, Johns Hopkins U) from 5/2017 to 4/2019. This study was approved by the IRB at each respective institution. Eligibility criteria included newly-diagnosed GBM pts ≥ 18 years of age with a tumor site that could be adequately imaged by sMRI. Cho/NAA ratio was normalized to the contralateral normal appearing white matter (NAWM). For RT planning, standard gross tumor volumes (GTV1 & 2) were defined based on T2-FLAIR and T1 CE MRIs and 5 mm margins were added to generate clinical tumor volumes (CTV1 & 2). GTV3 ( = CTV3, sMRI-defined) was generated by the union of residual CE tumor and Cho/NAA ≥ 2x NAWM. To remain eligible, CTV3 was required to be ≤ 65 cc. Planning target volumes (PTVs) were generated by applying a 3 mm margin around CTVs. 50.1, 60 and 75 Gy in 30 fractions were prescribed to PTV1, PTV2 and PTV3, respectively. All pts received standard concurrent/adjuvant TMZ. Survival curves were generated by the Kaplan-Meier method. Toxicities were assessed according to CTCAE v4.0. Results: 30 pts met eligibility and were treated on study. Mean/median ages were 56.4/58.9 years. 9 pts (30%) were MGMT methylated; 2 pts (6.7%) harbored an IDH1 mutation. With median followup of 21.4 months in censored pts, median OS was 23.0 months. 11 of 30 pts were documented to have experienced grade 3 or greater toxicities that were at least possibly due to their treatment. Of the 7 pts who experienced these by 9 months post-RT, most were attributable to TMZ (thrombocytopenia x 4, thrombocytopenia/neutropenia x 1, transaminitis x 1) and only one case (headaches/fatigue x 1) could potentially be ascribed to RT. Increased risk of pseudoprogression or radiation necrosis, especially beyond 3 months post-RT, was noted but these were clinically manageable and did not result in toxicity ≥ grade 3. Conclusions: Dose-escalated RT to 75 Gy guided by sMRI appears feasible and safe for pts with newly-diagnosed GBMs. OS outcome is also quite promising and warrants additional testing. Based on these results, a phase II randomized trial is planned at ECOG-ACRIN (EAF211). Clinical trial information: NCT03137888

Assessing Treatment Response of Glioblastoma to an HDAC Inhibitor Using Whole-Brain Spectroscopic MRI

Histone deacetylases regulate a wide variety of cellular functions and have been implicated in redifferentiation of various tumors. Histone deacetylase inhibitors (HDACi) are potential pharmacologic agents to improve outcomes for patients with gliomas. We assessed the therapeutic efficacy of belinostat (PXD-101), an HDACi with blood–brain barrier permeability. Belinostat was first tested in an orthotopic rat glioma model to assess in vivo tumoricidal effect. Our results showed that belinostat was effective in reducing tumor volume in the orthotopic rat glioma model in a dose-dependent manner. We also tested the antidepression activity of belinostat in 2 animal models of depression and found it to be effective. Furthermore, we confirmed that myo-inositol levels improved by belinostat treatment in vitro. In a human pilot study, it was observed that belinostat in combination with chemoradiation may delay initial recurrence of disease. Excitingly, belinostat significantly improved depressive symptoms in patients with glioblastoma compared with control subjects. Finally, spectroscopic magnetic resonance imaging of 2 patient cases from this pilot study are presented to indicate how spectroscopic magnetic resonance imaging can be used to monitor metabolite response and assess treatment effect on whole brain. This study highlights the potential of belinostat to be a synergistic therapeutic agent in the treatment of gliomas

Final Report on Clinical Outcomes and Tumor Recurrence Patterns of a Pilot Study Assessing Efficacy of Belinostat (PXD-101) with Chemoradiation for Newly Diagnosed Glioblastoma

Glioblastoma (GBM) is highly aggressive and has a poor prognosis. Belinostat is a histone deacetylase inhibitor with blood–brain barrier permeability, anti-GBM activity, and the potential to enhance chemoradiation. The purpose of this clinical trial was to assess the efficacy of combining belinostat with standard-of-care therapy. Thirteen patients were enrolled in each of control and belinostat cohorts. The belinostat cohort was given a belinostat regimen (500–750 mg/m2 1×/day × 5 days) every three weeks (weeks 0, 3, and 6 of RT). All patients received temozolomide and radiation therapy (RT). RT margins of 5–10 mm were added to generate clinical tumor volumes and 3 mm added to create planning target volumes. Median overall survival (OS) was 15.8 months for the control cohort and 18.5 months for the belinostat cohort (p = 0.53). The recurrence volumes (rGTVs) for the control cohort occurred in areas that received higher radiation doses than that in the belinostat cohort. For those belinostat patients who experienced out-of-field recurrence, tumors were detectable by spectroscopic MRI before RT. Recurrence analysis suggests better in-field control with belinostat. This study highlights the potential of belinostat as a synergistic therapeutic agent for GBM. It may be particularly beneficial to combine this radio-sensitizing effect with spectroscopic MRI-guided RT

A Novel Approach to Determining Tumor Progression Using a Three-Site Pilot Clinical Trial of Spectroscopic MRI-Guided Radiation Dose Escalation in Glioblastoma

Glioblastoma (GBM) is a fatal disease, with poor prognosis exacerbated by difficulty in assessing tumor extent with imaging. Spectroscopic MRI (sMRI) is a non-contrast imaging technique measuring endogenous metabolite levels of the brain that can serve as biomarkers for tumor extension. We completed a three-site study to assess survival benefits of GBM patients when treated with escalated radiation dose guided by metabolic abnormalities in sMRI. Escalated radiation led to complex post-treatment imaging, requiring unique approaches to discern tumor progression from radiation-related treatment effect through our quantitative imaging platform. The purpose of this study is to determine true tumor recurrence timepoints for patients in our dose-escalation multisite study using novel methodology and to report on median progression-free survival (PFS). Follow-up imaging for all 30 trial patients were collected, lesion volumes segmented and graphed, and imaging uploaded to our platform for visual interpretation. Eighteen months post-enrollment, the median PFS was 16.6 months with a median time to follow-up of 20.3 months. With this new treatment paradigm, incidence rate of tumor recurrence one year from treatment is 30% compared to 60-70% failure under standard care. Based on the delayed tumor progression and improved survival, a randomized phase II trial is under development (EAF211)