Additive Value of MR Simulation Prior to Chemoradiation in Evaluating Treatment Response and Pseudoprogression in High-Grade Gliomas.

BACKGROUND: A dedicated MRI Simulation(MRsim) for radiation treatment(RT) planning in high-grade glioma(HGG) patients can detect early radiological changes, including tumor progression after surgery and before standard of care chemoradiation. This study aimed to determine the impact of using post-op MRI vs. MRsim as the baseline for response assessment and reporting pseudo-progression on follow-up imaging at one month(FU1) after chemoradiation. METHODS: Histologically confirmed HGG patients were planned for six weeks of RT in a prospective study for adaptive RT planning. All patients underwent post-op MRI, MRsim, and follow-up MRI scans every 2-3 months. Tumor response was assessed by three independent blinded reviewers using Response Assessment in Neuro-Oncology(RANO) criteria when baseline was either post-op MRI or MRsim. Interobserver agreement was calculated using light's kappa. RESULTS: 30 patients (median age 60.5 years; IQR 54.5-66.3) were included. Median interval between surgery and RT was 34 days (IQR 27-41). Response assessment at FU1 differed in 17 patients (57%) when the baseline was post-op MRI vs. MRsim, including true progression vs. partial response(PR) or stable disease(SD) in 11 (37%) and SD vs. PR in 6 (20%) patients. True progression was reported in 19 patients (63.3%) on FU1 when the baseline was post-op MRI vs 8 patients (26.7%) when the baseline was MRsim (p=.004). Pseudo-progression was observed at FU1 in 12 (40%) vs. 4 (13%) patients, when the baseline was post-op MRI vs. MRsim (p=.019). Interobserver agreement between observers was moderate (κ = 0.579; p<0.001). CONCLUSIONS: Our study demonstrates the value of acquiring an updated MR closer to RT in patients with HGG to improve response assessment, and accuracy in evaluation of pseudo-progression even at the early time point of first follow-up after RT. Earlier identification of patients with true progression would enable more timely salvage treatments including potential clinical trial enrolment to improve patient outcomes.

Development and benchmarking diffusion magnetic resonance imaging analysis for integration into radiation treatment planning.

PURPOSE: The rising promise in the utility of advanced multi-parametric magnetic resonance (MR) imaging in radiotherapy (RT) treatment planning creates a necessity for testing and enhancing the accuracy of quantitative imaging analysis. Standardizing the analysis of diffusion weighted imaging (DWI) and diffusion tensor imaging (DTI) to generate meaningful and reproducible apparent diffusion coefficient (ADC) and fractional anisotropy (FA) lays the requisite needed for clinical integration. The aim of the demonstrated work is to benchmark the generation of the ADC and FA parametric map analyses using integrated tools in a commercial treatment planning system against the currently used ones. METHODS: Three software packages were used for generating ADC and FA maps in this study; one tool was developed within a commercial treatment planning system, another by the Functional Magnetic Resonance Imaging of the Brain (FMRIB) Software Library FSL (Analysis Group, FMRIB, Oxford, United Kingdom), and an in-house tool developed at the M.D. Anderson Cancer Center. The ADC and FA maps generated by all three packages for 35 subjects were subtracted from one another, and the standard deviation of the images' differences was used to compare the reproducibility. The reproducibility of the ADC maps was compared with the Quantitative Imaging Biomarkers Alliance (QIBA) protocol, while that of the FA maps was compared to data in published literature. RESULTS: Results show that the discrepancies between the ADC maps calculated for each patient using the three different software algorithms are less than 2% which meets the 3.6% recommended QIBA requirement. Except for a small number of isolated points, the majority of differences in FA maps for each patient produced by the three methods did not exceed 0.02 which is 10 times lower than the differences seen in healthy gray and white matter. The results were also compared to the maps generated by existing MR Imaging consoles and showed that the robustness of console generated ADC and FA maps is largely dependent on the correct application of scaling factors, that only if correctly placed; the differences between the three tested methods and the console generated values were within the recommended QIBA guidelines. CONCLUSIONS: Cross-comparison difference maps demonstrated that quantitative reproducibility of ADC and FA metrics generated using our tested commercial treatment planning system were comparable to in-house and established tools as benchmarks. This integrated approach facilitates the clinical utility of diffusion imaging in radiation treatment planning workflow.

Multifocal and multicentric glioblastoma: Imaging signature, molecular characterization, patterns of spread, and treatment.

Multifocal and multicentric glioblastoma (GBM) or collectively, m-GBM, is an imaging diagnosis present in up to 34% of patients with GBM. Compared to unifocal disease, patients with m-GBM have worse outcomes owing to the enhanced aggressive nature of the disease and its resistance to currently available treatments. To improve the understanding of its complex behavior, many associations have been established between the radiologic findings of m-GBM and its gross histology, genetic composition, and patterns of spread. Additionally, the holistic knowledge of the exact mechanisms of m-GBM genesis and progression is crucial for identifying potential targets permitting enhanced diagnosis and treatment. In this review, we aim to provide a comprehensive summary of the cumulative knowledge of the unique molecular biology and behavior of m-GBM and the association of these features with neuroimaging.

Automated Contouring and Planning in Radiation Therapy: What Is 'Clinically Acceptable'?

Developers and users of artificial-intelligence-based tools for automatic contouring and treatment planning in radiotherapy are expected to assess clinical acceptability of these tools. However, what is 'clinical acceptability'? Quantitative and qualitative approaches have been used to assess this ill-defined concept, all of which have advantages and disadvantages or limitations. The approach chosen may depend on the goal of the study as well as on available resources. In this paper, we discuss various aspects of 'clinical acceptability' and how they can move us toward a standard for defining clinical acceptability of new autocontouring and planning tools.

Opportunities for improving brain cancer treatment outcomes through imaging-based mathematical modeling of the delivery of radiotherapy and immunotherapy.

Immunotherapy has become a fourth pillar in the treatment of brain tumors and, when combined with radiation therapy, may improve patient outcomes and reduce the neurotoxicity. As with other combination therapies, the identification of a treatment schedule that maximizes the synergistic effect of radiation- and immune-therapy is a fundamental challenge. Mechanism-based mathematical modeling is one promising approach to systematically investigate therapeutic combinations to maximize positive outcomes within a rigorous framework. However, successful clinical translation of model-generated combinations of treatment requires patient-specific data to allow the models to be meaningfully initialized and parameterized. Quantitative imaging techniques have emerged as a promising source of high quality, spatially and temporally resolved data for the development and validation of mathematical models. In this review, we will present approaches to personalize mechanism-based modeling frameworks with patient data, and then discuss how these techniques could be leveraged to improve brain cancer outcomes through patient-specific modeling and optimization of treatment strategies.

Paradoxical Association Between Relative Cerebral Blood Volume Dynamics Following Chemoradiation and Increased Progression-Free Survival in Newly Diagnosed IDH Wild-Type MGMT Promoter Methylated Glioblastoma With Measurable Disease.

Background and Purpose: While relative cerebral blood volume (rCBV) may be diagnostic and prognostic for survival in glioblastoma (GBM), changes in rCBV during chemoradiation in the subset of newly diagnosed GBM with subtotal resection and the impact of MGMT promoter methylation status on survival have not been explored. This study aimed to investigate the association between rCBV response, MGMT methylation status, and progression-free (PFS) and overall survival (OS) in newly diagnosed GBM with measurable enhancing lesions. Methods: 1,153 newly diagnosed IDH wild-type GBM patients were screened and 53 patients (4.6%) had measurable post-surgical tumor (>1mL). rCBV was measured before and after patients underwent chemoradiation. Patients with a decrease in rCBV >10% were considered rCBV Responders, while patients with an increase or a decrease in rCBV <10% were considered rCBV Non-Responders. The association between change in enhancing tumor volume, change in rCBV, MGMT promotor methylation status, and PFS or OS were explored. Results: A decrease in tumor volume following chemoradiation trended towards longer OS (p=0.12; median OS=26.8 vs. 16.3 months). Paradoxically, rCBV Non-Responders had a significantly improved PFS compared to Responders (p=0.047; median PFS=9.6 vs. 7.2 months). MGMT methylated rCBV Non-Responders exhibited a significantly longer PFS compared to MGMT unmethylated rCBV Non-Responders (p<0.001; median PFS=0.5 vs. 7.1 months), and MGMT methylated rCBV Non-Responders trended towards longer PFS compared to methylated rCBV Responders (p=0.089; median PFS=20.5 vs. 13.8 months). Conclusions: This preliminary report demonstrates that in newly diagnosed IDH wild-type GBM with measurable enhancing disease after surgery (5% of patients), an enigmatic non-response in rCBV was associated with longer PFS, particularly in MGMT methylated patients.

Protocol for mathematical prediction of patient response and survival to immune checkpoint inhibitor immunotherapy.

This protocol describes the application of a mechanistic mathematical model of immune checkpoint inhibitor (ICI) immunotherapy to patient tumor imaging data for predicting solid tumor response and patient survival under ICI intervention. We describe steps for data collection and processing, data pipelines, and approaches to increase precision. The protocol is highly predictive as early as the first restaging after treatment start and can be used with standard-of-care imaging measures. For complete details on the use and execution of this protocol, please refer to Butner et al. (2020)1 and Butner et al. (2021).2.

Phase II trial of proton therapy versus photon IMRT for GBM: secondary analysis comparison of progression-free survival between RANO versus clinical assessment.

BACKGROUND: This secondary image analysis of a randomized trial of proton radiotherapy (PT) versus photon intensity-modulated radiotherapy (IMRT) compares tumor progression based on clinical radiological assessment versus Response Assessment in Neuro-Oncology (RANO). METHODS: Eligible patients were enrolled in the randomized trial and had MR imaging at baseline and follow-up beyond 12 weeks from completion of radiotherapy. "Clinical progression" was based on a clinical radiology report of progression and/or change in treatment for progression. RESULTS: Of 90 enrolled patients, 66 were evaluable. Median clinical progression-free survival (PFS) was 10.8 (range: 9.4-14.7) months; 10.8 months IMRT versus 11.2 months PT (P = .14). Median RANO-PFS was 8.2 (range: 6.9, 12): 8.9 months IMRT versus 6.6 months PT (P = .24). RANO-PFS was significantly shorter than clinical PFS overall (P = .001) and for both the IMRT (P = .01) and PT (P = .04) groups. There were 31 (46.3%) discrepant cases of which 17 had RANO progression more than a month prior to clinical progression, and 14 had progression by RANO but not clinical criteria. CONCLUSIONS: Based on this secondary analysis of a trial of PT versus IMRT for glioblastoma, while no difference in PFS was noted relative to treatment technique, RANO criteria identified progression more often and earlier than clinical assessment. This highlights the disconnect between measures of tumor response in clinical trials versus clinical practice. With growing efforts to utilize real-world data and personalized treatment with timely adaptation, there is a growing need to improve the consistency of determining tumor progression within clinical trials and clinical practice.

Foreign Body Ingestion Causing Recurrent Diverticulitis.

BACKGROUND Ingested foreign bodies (IFBs) are usually asymptomatic and are excreted uneventfully. IFBs become a major concern in elderly patients due to the increase number of diverticuloses where the foreign body can lodge and cause severe complications. CASE REPORT We report a case of an elderly patient who ingested a chicken bone that caused recurrent diverticulitis. CONCLUSIONS The diagnosis of complicated IFB cases is challenging, requires physician clinical expertise, and must be considered in individuals at risk.