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SuppFigure3. Stable suppression of PKM2 expression in G55 cells significantly alters intra-cellular concentrations of pyruvate and lactate. (*, p

Improvements in air quality have led to ecosystem recovery from acidic deposition, but the mechanisms and trajectories of this recovery are not fully understood. Here, we present long-term stream response and recovery data for paired watersheds at the Bear Brook Watershed in Maine (BBWM) during declining ambient SO4 and NO3 in precipitation. East Bear (EB) received ambient deposition from 1989 to 2018; West Bear (WB) received artificially elevated N + S from 1989 to 2016. The WB treatment was discontinued after 2016, the beginning of the recovery from both the experimental N + S and ambient decline. Stream SO4 in WB gradually declined after the treatment ended, from ~147 μeq L−1 in 2010–16 to ~126 μeq L−1 in 2017–18. The declining S inputs induced desorption of SO4 from soil phase surfaces, with stream loss far exceeding precipitation input. At the current rate of recovery, it will be many decades before the WB stream returns to pre-treatment SO4 concentrations. In contrast, NO3 is only weakly adsorbed in soil, and WB stream NO3 concentrations rapidly declined from ~39 μeq L−1 in 2010–16 to ~5 μeq L−1 in 2017–18, comparable to the N-limited EB stream. The acid anions are strongly coupled to base cation chemistry in streams, and there was a distinct hysteretic response of Ca and Mg to the chronic acidification, as (Ca + Mg) increased rapidly during the initial years, followed by declining values due to depletion of the soil exchange complex. This 30-year monitoring study (1989–2019) provides insights into recovery mechanisms from acidic deposition and highlights the role of abiotic processes in soil that mediate nutrient cycling and retention. Documenting the rapid response of N alongside the slower recovery for S identifies the temporal resolution necessary for other whole-watershed recovery studies.

We conducted a national-scale assessment of mercury (Hg) bioaccumulation in aquatic ecosystems, using dragonfly larvae as biosentinels, by developing a citizen-science network to facilitate biological sampling. Implementing a carefully designed sampling methodology for citizen scientists, we developed an effective framework for a landscape-level inquiry that might otherwise be resource limited. We assessed the variation in dragonfly Hg concentrations across >450 sites spanning 100 United States National Park Service units and examined intrinsic and extrinsic factors associated with the variation in Hg concentrations. Mercury concentrations ranged between 10.4 and 1411 ng/g dry weight across sites and varied among habitat types. Dragonfly total Hg (THg) concentrations were up to 1.8-fold higher in lotic habitats than in lentic habitats and 37% higher in waterbodies with abundant wetlands along their margins than those without wetlands. Mercury concentrations in dragonflies differed among families but were correlated (r2 > 0.80) with each other, enabling adjustment to a consistent family to facilitate spatial comparisons among sampling units. Dragonfly THg concentrations were positively correlated with THg concentrations in both fish and amphibians from the same locations, indicating that dragonfly larvae are effective indicators of Hg bioavailability in aquatic food webs. We used these relationships to develop an integrated impairment index of Hg risk to aquatic ecosytems and found that 12% of site-years exceeded high or severe benchmarks of fish, wildlife, or human health risk. Collectively, this continental-scale study demonstrates the utility of dragonfly larvae for estimating the potential mercury risk to fish and wildlife in aquatic ecosystems and provides a framework for engaging citizen science as a component of landscape Hg monitoring programs.

Mercury (Hg) is a toxic pollutant, widespread in northeastern U.S. ecosystems. Resource managers’ efforts to develop fish consumption advisories for humans and to focus conservation efforts for fish-eating wildlife are hampered by spatial variability. Dragonfly larvae can serve as biosentinels for Hg given that they are widespread in freshwaters, long-lived, exhibit site fidelity, and bioaccumulate relatively high mercury concentrations, mostly as methylmercury (88% ±11% MeHg in this study). We sampled lake water and dragonfly larvae in 74 northeastern US lakes that are part of the U.S. EPA Long-Term Monitoring Network, including 45 lakes in New York, 43 of which are in the Adirondacks. Aqueous dissolved organic carbon (DOC) and total Hg (THg) were strongly related to MeHg in lake water. Dragonfly larvae total mercury ranged from 0.016–0.918 μg/g, dw across the study area; Adirondack lakes had the minimum and maximum concentrations. Aqueous MeHg and dragonfly THg were similar between the Adirondack and Northeast regions, but a majority of lakes within the highest quartile of dragonfly THg were in the Adirondacks. Using landscape, lake chemistry, and lake morphometry data, we evaluated relationships with MeHg in lake water and THg in dragonfly larvae. Lakewater DOC and lake volume were strong predictors for MeHg in water. Dragonfly THg Bioaccumulation Factors (BAFs, calculated as [dragonfly THg]:[aqueous MeHg]) increased as lake volume increased, suggesting that lake size influences Hg bioaccumulation or biomagnification. BAFs declined with increasing DOC, supporting a potential limiting effect for MeHg bioavailability with higher DOC.

“Weather whiplash” is a colloquial phrase for describing an extreme event that includes shifts between two opposing weather conditions. Prior media coverage and research on these types of extremes have largely ignored winter weather events. However, rapid swings in winter weather can result in crossing from frozen to unfrozen conditions, or vice versa; thus, the potential impact of these types of events on coupled human and natural systems may be large. Given rapidly changing winter conditions in seasonally snow‐covered regions, there is a pressing need for a deeper understanding of such events and the extent of their impacts to minimize their risks. Here we introduce the concept of winter weather whiplash, defined as a class of extreme event in which a collision of unexpected conditions produces a forceful, rapid, back‐and‐forth change in winter weather that induces an outsized impact on coupled human and natural systems. Using a series of case studies, we demonstrate that the effects of winter weather whiplash events depend on the natural and human context in which they occur, and discuss how these events may result in the restructuring of social and ecological systems. We use the long‐term hydrometeorological record at the Hubbard Brook Experimental Forest in New Hampshire, USA to demonstrate quantitative methods for delineating winter weather whiplash events and their biophysical impacts. Ultimately, we argue that robust conceptual and quantitative frameworks for understanding winter weather whiplash events will contribute to the ways in which we mitigate and adapt to winter climate change in vulnerable regions.

Objective The Recruitment Innovation Center (RIC), partnering with the Trial Innovation Network and institutions in the National Institutes of Health-sponsored Clinical and Translational Science Awards (CTSA) Program, aimed to develop a service line to retrieve study population estimates from electronic health record (EHR) systems for use in selecting enrollment sites for multicenter clinical trials. Our goal was to create and field-test a low burden, low tech, and high-yield method. Materials and Methods In building this service line, the RIC strove to complement, rather than replace, CTSA hubs’ existing cohort assessment tools. For each new EHR cohort request, we work with the investigator to develop a computable phenotype algorithm that targets the desired population. CTSA hubs run the phenotype query and return results using a standardized survey. We provide a comprehensive report to the investigator to assist in study site selection. Results From 2017 to 2020, the RIC developed and socialized 36 phenotype-dependent cohort requests on behalf of investigators. The average response rate to these requests was 73%. Discussion Achieving enrollment goals in a multicenter clinical trial requires that researchers identify study sites that will provide sufficient enrollment. The fast and flexible method the RIC has developed, with CTSA feedback, allows hubs to query their EHR using a generalizable, vetted phenotype algorithm to produce reliable counts of potentially eligible study participants. Conclusion The RIC’s EHR cohort assessment process for evaluating sites for multicenter trials has been shown to be efficient and helpful. The model may be replicated for use by other programs.

PURPOSE To compare the performance of an 8-channel surface coil/clamshell transmitter and 32-channel head array coil/birdcage transmitter for hyperpolarized 13 C brain metabolic imaging. METHODS To determine the field homogeneity of the radiofrequency transmitters, B1 + mapping was performed on an ethylene glycol head phantom and evaluated by means of the double angle method. Using a 3D echo-planar imaging sequence, coil sensitivity and noise-only phantom data were acquired with the 8- and 32-channel receiver arrays, and compared against data from the birdcage in transceiver mode. Multislice frequency-specific 13 C dynamic echo-planar imaging was performed on a patient with a brain tumor for each hardware configuration following injection of hyperpolarized [1-13 C]pyruvate. Signal-to-noise ratio (SNR) was evaluated from pre-whitened phantom and temporally summed patient data after coil combination based on optimal weights. RESULTS The birdcage transmitter produced more uniform B1 + compared with the clamshell: 0.07 versus 0.12 (fractional error). Phantom experiments conducted with matched lateral housing separation demonstrated 8- versus 32-channel mean transceiver-normalized SNR performance: 0.91 versus 0.97 at the head center; 6.67 versus 2.08 on the sides; 0.66 versus 2.73 at the anterior; and 0.67 versus 3.17 on the posterior aspect. While the 8-channel receiver array showed SNR benefits along lateral aspects, the 32-channel array exhibited greater coverage and a more uniform coil-combined profile. Temporally summed, parameter-normalized patient data showed SNRmean,slice ratios (8-channel/32-channel) ranging 0.5-2.00 from apical to central brain. White matter lactate-to-pyruvate ratios were conserved across hardware: 0.45 ± 0.12 (8-channel) versus 0.43 ± 0.14 (32-channel). CONCLUSION The 8- and 32-channel hardware configurations each have advantages in particular brain anatomy.

Proton Magnetic Resonance Spectroscopy ((1)H MRS) provides non-invasive, quantitative metabolite profiles of tissue and has been shown to aid the clinical management of several brain diseases. Whilst most modern clinical MR scanners support MRS capabilities, routine use is largely restricted to specialized centers with good access to MR research support. Widespread adoption has been slow for several reasons, and technical challenges towards obtaining reliable good-quality results have been identified as a contributing factor. Considerable progress has been made by the research community to address many of these challenges, and in this paper a consensus is presented on deficiencies in widely available MRS methodology and validated improvements that are currently in routine use at several clinical research institutions. In particular, the localization error for the popular point resolved spectroscopy (PRESS) localization sequence was found to be unacceptably high at 3T, and the use of the semi-adiabatic localization by adiabatic selective refocusing (semi-LASER) sequence is a recommended solution. The incorporation of simulated metabolite basis-sets into analysis routines is recommended for reliably capturing the full spectral detail available from short echo time acquisitions. In addition, the importance of achieving a highly homogenous static magnetic field (B(0)) in the acquisition region is emphasized, and the limitations of current methods and hardware are discussed. Most recommendations require only software improvements, greatly enhancing the capabilities of clinical MRS on existing hardware. We anticipate the implementation of these recommendations will strengthen current clinical applications and advance progress towards developing and validating new MRS biomarkers for clinical use.

This white paper discusses prospects for advancing hyperpolarization technology to better understand cancer metabolism, identify current obstacles to HP (hyperpolarized) 13C magnetic resonance imaging’s (MRI’s) widespread clinical use, and provide recommendations for overcoming them. Since the publication of the first NIH white paper on hyperpolarized 13C MRI in 2011, preclinical studies involving [1-13C]pyruvate as well a number of other 13C labeled metabolic substrates have demonstrated this technology's capacity to provide unique metabolic information. A dose-ranging study of HP [1-13C]pyruvate in patients with prostate cancer established safety and feasibility of this technique. Additional studies are ongoing in prostate, brain, breast, liver, cervical, and ovarian cancer. Technology for generating and delivering hyperpolarized agents has evolved, and new MR data acquisition sequences and improved MRI hardware have been developed. It will be important to continue investigation and development of existing and new probes in animal models. Improved polarization technology, efficient radiofrequency coils, and reliable pulse sequences are all important objectives to enable exploration of the technology in healthy control subjects and patient populations. It will be critical to determine how HP 13C MRI might fill existing needs in current clinical research and practice, and complement existing metabolic imaging modalities. Financial sponsorship and integration of academia, industry, and government efforts will be important factors in translating the technology for clinical research in oncology. This white paper is intended to provide recommendations with this goal in mind.

Magnetic resonance spectroscopic imaging (MRSI) offers considerable promise for monitoring metabolic alterations associated with disease or injury; however, to date, these methods have not had a significant impact on clinical care, and their use remains largely confined to the research community and a limited number of clinical sites. The MRSI methods currently implemented on clinical MRI instruments have remained essentially unchanged for two decades, with only incremental improvements in sequence implementation. During this time, a number of technological developments have taken place that have already greatly benefited the quality of MRSI measurements within the research community and which promise to bring advanced MRSI studies to the point where the technique becomes a true imaging modality, while making the traditional review of individual spectra a secondary requirement. Furthermore, the increasing use of biomedical MR spectroscopy studies has indicated clinical areas where advanced MRSI methods can provide valuable information for clinical care. In light of this rapidly changing technological environment and growing understanding of the value of MRSI studies for biomedical studies, this article presents a consensus from a group of experts in the field that reviews the state-of-the-art for clinical proton MRSI studies of the human brain, recommends minimal standards for further development of vendor-provided MRSI implementations, and identifies areas which need further technical development.

Clinical trials continue to face significant challenges in participant recruitment and retention. The Recruitment Innovation Center (RIC), part of the Trial Innovation Network (TIN), has been funded by the National Center for Advancing Translational Sciences of the National Institutes of Health to develop innovative strategies and technologies to enhance participant engagement in all stages of multicenter clinical trials. In collaboration with investigator teams and liaisons at Clinical and Translational Science Award institutions, the RIC is charged with the mission to design, field-test, and refine novel resources in the context of individual clinical trials. These innovations are disseminated via newsletters, publications, a virtual toolbox on the TIN website, and RIC-hosted collaboration webinars. The RIC has designed, implemented, and promised customized recruitment support for 173 studies across many diverse disease areas. This support has incorporated site feasibility assessments, community input sessions, recruitment materials recommendations, social media campaigns, and an array of study-specific suggestions. The RIC’s goal is to evaluate the efficacy of these resources and provide access to all investigating teams, so that more trials can be completed on time, within budget, with diverse participation, and with enough accrual to power statistical analyses and make substantive contributions to the advancement of healthcare.

The Dragonfly Mercury Project (DMP) is a dynamic national scale program coupling scientific efforts to understand mercury pollution risks to protected areas with citizen engagement and education. W...

The vernal transition represents the seasonal transition to spring, occurring as temperatures rise at the end of winter. With rapid snowmelt, microbial community turnover, and accelerated nutrient cycling, this is a critical but relatively under-studied period of ecosystem function. We conducted a study over two consecutive winters (2015-2016) at the Bear Brook Watershed in Maine to examine how changing winter conditions (warming winters, reduced snow accumulation) altered soil nitrogen availability and stream N export during winter and the vernal transition, and how these patterns were influenced by ecosystem N status (N-enriched vs. N-limited). Of the two study years, 2016 had a warmer winter with substantially less snow accumulation and a discontinuous snowpack-and as a result, had a longer vernal transition and a snowpack that thawed before the vernal transition began. Across both years, snowmelt triggered a transition, signaled by increased ammonium concentrations in soil, decreased soil nitrate concentrations due to flushing by meltwater, and increased stream nitrate exports. Despite the contrasting winter conditions, both years showed similar patterns in N availability and export, differing only in the timing of these transitions. The vernal transition has conventionally been considered a critical period for biogeochemical cycling, because the associated snowmelt event triggers physicochemical and biochemical changes in soil systems. This was consistent with our results in 2015, but our data for 2016 show that this may not always hold true, and instead, that warmer, low-snow winters may demonstrate a temporal asynchrony between snowmelt and the vernal transition. We also show that ecosystem N status is a strong driver of the seasonal N pattern, and the interaction of N status and changing climate must be further investigated to understand ecosystem function under our current predicted trajectory of warming winters, declining snowfall, and winter thaw events.

The vernal transition represents the seasonal transition to spring, occurring as temperatures rise at the end of winter. With rapid snowmelt, microbial community turnover, and accelerated nutrient cycling, this is a critical but relatively under-studied period of ecosystem function. We conducted a study over two consecutive winters (2015-2016) at the Bear Brook Watershed in Maine to examine how changing winter conditions (warming winters, reduced snow accumulation) altered soil nitrogen availability and stream N export during winter and the vernal transition, and how these patterns were influenced by ecosystem N status (N-enriched vs. N-limited). Of the two study years, 2016 had a warmer winter with substantially less snow accumulation and a discontinuous snowpack-and as a result, had a longer vernal transition and a snowpack that thawed before the vernal transition began. Across both years, snowmelt triggered a transition, signaled by increased ammonium concentrations in soil, decreased soil nitrate concentrations due to flushing by meltwater, and increased stream nitrate exports. Despite the contrasting winter conditions, both years showed similar patterns in N availability and export, differing only in the timing of these transitions. The vernal transition has conventionally been considered a critical period for biogeochemical cycling, because the associated snowmelt event triggers physicochemical and biochemical changes in soil systems. This was consistent with our results in 2015, but our data for 2016 show that this may not always hold true, and instead, that warmer, low-snow winters may demonstrate a temporal asynchrony between snowmelt and the vernal transition. We also show that ecosystem N status is a strong driver of the seasonal N pattern, and the interaction of N status and changing climate must be further investigated to understand ecosystem function under our current predicted trajectory of warming winters, declining snowfall, and winter thaw events.

BackgroundDifferentiating treatment-induced injury from recurrent high-grade glioma is an ongoing challenge in neuro-oncology, in part due to lesion heterogeneity. This study aimed to determine whether different MR features were relevant for distinguishing recurrent tumor from the effects of treatment in contrast-enhancing lesions (CEL) and non-enhancing lesions (NEL).MethodsThis prospective study analyzed 291 tissue samples (222 recurrent tumor, 69 treatment-effect) with known coordinates on imaging from 139 patients who underwent preoperative 3T MRI and surgery for a suspected recurrence. 8 MR parameter values were tested from perfusion-weighted, diffusion-weighted, and MR spectroscopic imaging at each tissue sample location for association with histopathological outcome using generalized estimating equation models for CEL and NEL tissue samples. Individual cutoff values were evaluated using receiver operating characteristic curve analysis with 5-fold cross-validation.ResultsIn tissue samples obtained from CEL, elevated relative cerebral blood volume (rCBV) was associated with the presence of recurrent tumor pathology (P < 0.03), while increases in normalized choline (nCho) and choline-to-NAA index (CNI) were associated with the presence of recurrent tumor pathology in NEL tissue samples (P < 0.008). A mean CNI cutoff value of 2.7 had the highest performance, resulting in mean sensitivity and specificity of 0.61 and 0.81 for distinguishing treatment-effect from recurrent tumor within the NEL.ConclusionAlthough our results support prior work that underscores the utility of rCBV in distinguishing the effects of treatment from recurrent tumor within the contrast enhancing lesion, we found that metabolic parameters may be better at differentiating recurrent tumor from treatment-related changes in the NEL of high-grade gliomas.

Climate change in northeastern North America is resulting in warmer winters with reduced snow accumulation. Soils under a thin snowpack are more likely to experience freeze–thaw cycles, disrupting carbon (C) and nitrogen (N) transformations. We conducted a 2 year snow removal experiment in Maine to study the effects of soil freezing on soil C and N processes. O horizon soils were sampled during winter and spring of 2015 and 2016, and they were analyzed for labile inorganic N and water-extractable organic carbon (WEOC) concentrations, specific ultraviolet absorbance (SUVA254), and potential net N mineralization. The winter of 2015 was cold and snowy, whereas 2016 was warm with a shallow, short-term snowpack. Snow removal caused the soils to freeze, but winter rain-on-soil events in 2015 resulted in the formation of concrete frost, as opposed to granular frost in 2016. Concrete frost increased soil ammonium (NH4+-N) and WEOC concentrations and decreased SUVA254, which we attribute to microbial cell lysis. In contrast, granular frost did not alter soil nutrient concentrations, reflecting limited microbial distress. Our study demonstrates that moisture content influences the intensity of soil freezing, highlighting the importance of snowpack depth and winter rain events in regulating winter and spring biogeochemical processes and nutrient availability.

The USA has set aside over 400 national parks and other protected areas to be managed by the National Park Service (NPS). Collectively, these sites attract over 300 million visits per year which makes the NPS one of the largest informal education institutions in the country. Because the NPS supports and facilitates scientific studies in parks, the national park system provides abundant opportunity for biologists and other scientists to engage global audiences in learning, exploring, and even conducting science. Those opportunities are best pursued through collaborations among scientists and the professional communication staff (interpreters, educators, media specialists, etc.) of parks and their partner organizations. This article describes unique opportunities and rationale for such collaborations, presents several examples that highlight the range of activities and lessons drawn from them, and invites scientists to conduct studies in parks and bring their science into the public eye.

Purpose The purpose of this study was to develop a new 3D dynamic carbon-13 compressed sensing echoplanar spectroscopic imaging (EPSI) MR sequence and test it in phantoms, animal models, and then in prostate cancer patients to image the metabolic conversion of hyperpolarized [1-13 C]pyruvate to [1-13 C]lactate with whole gland coverage at high spatial and temporal resolution. Methods A 3D dynamic compressed sensing (CS)-EPSI sequence with spectral-spatial excitation was designed to meet the required spatial coverage, time and spatial resolution, and RF limitations of the 3T MR scanner for its clinical translation for prostate cancer patient imaging. After phantom testing, animal studies were performed in rats and transgenic mice with prostate cancers. For patient studies, a GE SPINlab polarizer (GE Healthcare, Waukesha, WI) was used to produce hyperpolarized sterile GMP [1-13 C]pyruvate. 3D dynamic 13 C CS-EPSI data were acquired starting 5 s after injection throughout the gland with a spatial resolution of 0.5 cm3 , 18 time frames, 2-s temporal resolution, and 36 s total acquisition time. Results Through preclinical testing, the 3D CS-EPSI sequence developed in this project was shown to provide the desired spectral, temporal, and spatial 5D HP 13 C MR data. In human studies, the 3D dynamic HP CS-EPSI approach provided first-ever simultaneously volumetric and dynamic images of the LDH-catalyzed conversion of [1-13 C]pyruvate to [1-13 C]lactate in a biopsy-proven prostate cancer patient with full gland coverage. Conclusion The results demonstrate the feasibility to characterize prostate cancer metabolism in animals, and now patients using this new 3D dynamic HP MR technique to measure kPL , the kinetic rate constant of [1-13 C]pyruvate to [1-13 C]lactate conversion.

Author(s): Park, Ilwoo; Larson, Peder EZ; Gordon, Jeremy W; Carvajal, Lucas; Chen, Hsin-Yu; Bok, Robert; Van Criekinge, Mark; Ferrone, Marcus; Slater, James B; Xu, Duan; Kurhanewicz, John; Vigneron, Daniel B; Chang, Susan; Nelson, Sarah J | Abstract: Purpose: Hyperpolarized carbon-13 (13C) metabolic imaging is a noninvasive imaging modality for evaluating real-time metabolism. The purpose of this study was to develop and implement experimental strategies for using [1-13C]pyruvate to probe in vivo metabolism for patients with brain tumors and other neurological diseases. Methods: The 13C radiofrequency coils and pulse sequences were tested in a phantom and were performed using a 3 Tesla whole-body scanner. Samples of [1-13C]pyruvate were polarized using a SPINlab system. Dynamic 13C data were acquired from 8 patients previously diagnosed with brain tumors, who had received treatment and were being followed with serial magnetic resonance scans. Results: The phantom studies produced good-quality spectra with a reduction in signal intensity in the center attributed to the reception profiles of the 13C receive coils. Dynamic data obtained from a 3-cm slice through a patient's brain following injection with [1-13C]pyruvate showed the anticipated arrival of the agent, its conversion to lactate and bicarbonate, and subsequent reduction in signal intensity. A similar temporal pattern was observed in 2D dynamic patient studies, with signals corresponding to pyruvate, lactate, and bicarbonate being in normal appearing brain, but only pyruvate and lactate being detected in regions corresponding to the anatomical lesion. Physiological monitoring and follow-up confirmed that there were no adverse events associated with the injection. Conclusion: This study has presented the first application of hyperpolarized 13C metabolic imaging in patients with brain tumor and demonstrated the safety and feasibility of using hyperpolarized [1-13C]pyruvate to evaluate in vivo brain metabolism. Magn Reson Med 80:864–873, 2018. © 2018 International Society for Magnetic Resonance in Medicine.

BACKGROUND Activation of the phosphatidylinositol 3-kinase (PI3K)/mammalian target of rapamycin (mTOR) pathway is common in patients with low-grade gliomas (LGGs), but agents that inhibit this pathway, including mTOR inhibitors, have not been studied in this population. METHODS Fifty-eight patients with pathologic evidence of recurrence after they had initially been diagnosed with World Health Organization (WHO) grade II gliomas were enrolled into a prospective phase 2 clinical trial and received daily everolimus (RAD001) for 1 year or until progression. Tissue at the time of enrollment was analyzed for markers of PI3K/mTOR pathway activation. Thirty-eight patients underwent serial multiparametric magnetic resonance imaging, with the tumor volume and the perfusion metrics (the fractional blood volume [fBV] for capillary density and the transfer coefficient [Kps ] for vascular permeability) measured during treatment. The primary endpoint was progression-free survival at 6 months (PFS-6) in patients with WHO II disease at enrollment. RESULTS For patients with WHO II gliomas at enrollment, the PFS-6 rate was 84%, and this met the primary endpoint (P

Purpose To implement a fully automated atlas-based method for prescribing 3D PRESS MR spectroscopic imaging (MRSI). Methods The PRESS selected volume and outer-volume suppression bands were predefined on the MNI152 standard template image. The template image was aligned to the subject T1-weighted image during a scan, and the resulting transformation was then applied to the predefined prescription. To evaluate the method, H-1 MRSI data were obtained in repeat scan sessions from 20 healthy volunteers. In each session, datasets were acquired twice without repositioning. The overlap ratio of the prescribed volume in the two sessions was calculated and the reproducibility of inter- and intrasession metabolite peak height and area ratios was measured by the coefficient of variation (CoV). The CoVs from intra- and intersession were compared by a paired t-test. Results The average overlap ratio of the automatically prescribed selection volumes between two sessions was 97.8%. The average voxel-based intersession CoVs were less than 0.124 and 0.163 for peak height and area ratios, respectively. Paired t-test showed no significant difference between the intra- and intersession CoVs. Conclusion The proposed method provides a time efficient method to prescribe 3D PRESS MRSI with reproducible imaging positioning and metabolite measurements. Magn Reson Med, 2017. © 2017 The Authors Magnetic Resonance in Medicine published by Wiley Periodicals, Inc. on behalf of International Society for Magnetic Resonance in Medicine. This is an open access article under the terms of the Creative Commons Attribution-NonCommercial-NoDerivs License, which permits use and distribution in any medium, provided the original work is properly cited, the use is non-commercial and no modifications or adaptations are made.

OBJECTIVES/GOALS: Innovations with positive health impact are a high priority for NCATS and CTSAs. Program design that uses the Causal Pathway approach incorporates performance indicators that assess impact. We applied Causal Pathway thinking to an ongoing national program to enhance the evaluation of program impact. We report Lessons Learned. METHODS/STUDY POPULATION: We conducted a day-long onsite workshop to introduce the model to the project team, build capacity, and map the existing program elements to Logic Models representing program Specific Aims. A local Causal Pathway (CP) champion was identified. Alignment of the Logic Models with the CP approach (input→activities→ outputs→effects/impact) developed iteratively through biweekly, then monthly conferral among stakeholders. Key tasks included distinguishing among activities, outputs, and effects (impacts), and identification of performance indicators for each stage of the Causal Pathway. Visualization tools and an additional late stage half-day workshop were used to foster consensus. Implementation of the CP model tested the feasibility of collecting specific indicators and prompted model revisions. RESULTS/ANTICIPATED RESULTS: Program leadership and team members (n = 30) participated in the kick-off workshop. Four Specific Aims were mapped to Logic Models. Multiple Causal Pathway (CP) diagrams, one for each project in the program, were developed and mapped to Aims. Alignment of CP threads to Aims and identification of performance indicators required iteration. CP threads converged onto common final Impacts, sometimes crossing to another Aim. Performance indicators for operations were readily accessible to team members, and less so for impacts. Assumptions about program effects were subjected to specific indicators. Over time, Leadership noticed more expression of CP thinking in daily activities. New projects developed during this period incorporated the CP approach. Teams were able to streamline and simplify Logic/CP models. DISCUSSION/SIGNIFICANCE OF IMPACT: Through capacity-building and mentored exercises, an innovation team was able to infuse CP thinking into the evaluation of their ongoing program. The CP approach to design and evaluation maps progress and indicators across the life of a program from initial activities to its ultimate impact.

Background:To identify potential participants for clinical trials, electronic health records (EHRs) are searched at potential sites. As an alternative, we investigated using medical devices used for real-time diagnostic decisions for trial enrollment.Methods:To project cohorts for a trial in acute coronary syndromes (ACS), we used electrocardiograph-based algorithms that identify ACS or ST elevation myocardial infarction (STEMI) that prompt clinicians to offer patients trial enrollment. We searched six hospitals’ electrocardiograph systems for electrocardiograms (ECGs) meeting the planned trial’s enrollment criterion: ECGs with STEMI or > 75% probability of ACS by the acute cardiac ischemia time-insensitive predictive instrument (ACI-TIPI). We revised the ACI-TIPI regression to require only data directly from the electrocardiograph, the e-ACI-TIPI using the same data used for the original ACI-TIPI (development set n = 3,453; test set n = 2,315). We also tested both on data from emergency department electrocardiographs from across the US (n = 8,556). We then used ACI-TIPI and e-ACI-TIPI to identify potential cohorts for the ACS trial and compared performance to cohorts from EHR data at the hospitals.Results:Receiver-operating characteristic (ROC) curve areas on the test set were excellent, 0.89 for ACI-TIPI and 0.84 for the e-ACI-TIPI, as was calibration. On the national electrocardiographic database, ROC areas were 0.78 and 0.69, respectively, and with very good calibration. When tested for detection of patients with > 75% ACS probability, both electrocardiograph-based methods identified eligible patients well, and better than did EHRs.Conclusion:Using data from medical devices such as electrocardiographs may provide accurate projections of available cohorts for clinical trials.

Winter is an understudied but key period for the socioecological systems of northeastern North American forests. A growing awareness of the importance of the winter season to forest ecosystems and surrounding communities has inspired several decades of research, both across the northern forest and at other mid‐ and high‐latitude ecosystems around the globe. Despite these efforts, we lack a synthetic understanding of how winter climate change may impact hydrological and biogeochemical processes and the social and economic activities they support. Here, we take advantage of 100 years of meteorological observations across the northern forest region of the northeastern United States and eastern Canada to develop a suite of indicators that enable a cross‐cutting understanding of (1) how winter temperatures and snow cover have been changing and (2) how these shifts may impact both ecosystems and surrounding human communities. We show that cold and snow covered conditions have generally decreased over the past 100 years. These trends suggest positive outcomes for tree health as related to reduced fine root mortality and nutrient loss associated with winter frost but negative outcomes as related to the northward advancement and proliferation of forest insect pests. In addition to effects on vegetation, reductions in cold temperatures and snow cover are likely to have negative impacts on the ecology of the northern forest through impacts on water, soils, and wildlife. The overall loss of coldness and snow cover may also have negative consequences for logging and forest products, vector‐borne diseases, and human health, recreation, and tourism, and cultural practices, which together represent important social and economic dimensions for the northern forest region. These findings advance our understanding of how our changing winters may transform the socioecological system of a region that has been defined by the contrasting rhythm of the seasons. Our research also identifies a trajectory of change that informs our expectations for the future as the climate continues to warm.

PURPOSE: The purpose of this study was to compare C-13 imaging parameters with hyperpolarized [1-(13)C]pyruvate with conventional gadolinium (Gd)-based perfusion weighted imaging using an orthotopic xenograft model of human glioblastoma multiforme (GBM). PROCEDURES: C-13 3D magnetic resonance spectroscopic imaging (MRSI) data were obtained from 14 tumor-bearing rats after the injection of hyperpolarized [1-(13)C]pyruvate at a 3T scanner. Dynamic susceptibility contrast (DSC) perfusion-weighted MR images were obtained following intravenous administration of Gd-DTPA. Normalized lactate, pyruvate, total carbon, and lactate to pyruvate ratio from C-13 MRSI data were compared with normalized peak height and percent recovery of ΔR2* curve from the DSC images in the voxels containing tumor using a Pearson’s linear correlation. RESULTS: Normalized peak height from DSC imaging showed substantial correlations with normalized lactate (r = 0.6, p = 0.02) and total carbon (r = 0.6, p = 0.02) from hyperpolarized C-13 MRSI data. CONCLUSIONS: Since the peak height in the ΔR2* curve from DSC data is related to the extent of blood volume, these hyperpolarized C-13 imaging parameters may be used to assess blood volume in rodent intracranial xenograft models of GBM.

Glioma is recognized to be a highly heterogeneous CNS malignancy, whose diverse cellular composition and cellular interactions have not been well characterized. To gain new clinical- and biological-insights into the genetically-bifurcated IDH1 mutant (mt) vs wildtype (wt) forms of glioma, we integrated multiplexed immunofluorescence single cell data for 43 protein markers across cancer hallmarks, in addition to cell spatial metrics, genomic sequencing and magnetic resonance imaging (MRI) quantitative features. Molecular and spatial heterogeneity scores for angiogenesis and cell invasion differ between IDHmt and wt gliomas irrespective of prior treatment and tumor grade; these differences also persisted in the MR imaging features of peritumoral edema and contrast enhancement volumes. Longer overall survival for IDH1mt glioma patients may reflect generalized altered cellular, molecular, spatial heterogeneity which manifest in discernable radiological manifestations.

Glioma is recognized to be a highly heterogeneous CNS malignancy, whose diverse cellular composition and cellular interactions have not been well characterized. To gain new clinical- and biological-insights into the genetically-bifurcated IDH1 mutant (mt) vs wildtype (wt) forms of glioma, we integrated data from protein, genomic and MR imaging from 20 treatment-naïve glioma cases and 16 recurrent GBM cases. Multiplexed immunofluorescence (MxIF) was used to generate single cell data for 43 protein markers representing all cancer hallmarks, Genomic sequencing (exome and RNA (normal and tumor) and magnetic resonance imaging (MRI) quantitative features (protocols were T1-post, FLAIR and ADC) from whole tumor, peritumoral edema and enhancing core vs equivalent normal region were also collected from patients. Based on MxIF analysis, 85,767 cells (glioma cases) and 56,304 cells (GBM cases) were used to generate cell-level data for 24 biomarkers. K-means clustering was used to generate 7 distinct groups of cells with divergent biomarker profiles and deconvolution was used to assign RNA data into three classes. Spatial and molecular heterogeneity metrics were generated for the cell data. All features were compared between IDH mt and IDHwt patients and were finally combined to provide a holistic/integrated comparison. Protein expression by hallmark was generally lower in the IDHmt vs wt patients. Molecular and spatial heterogeneity scores for angiogenesis and cell invasion also differed between IDHmt and wt gliomas irrespective of prior treatment and tumor grade; these differences also persisted in the MR imaging features of peritumoral edema and contrast enhancement volumes. A coherent picture of enhanced angiogenesis in IDHwt tumors was derived from multiple platforms (genomic, proteomic and imaging) and scales from individual proteins to cell clusters and heterogeneity, as well as bulk tumor RNA and imaging features. Longer overall survival for IDH1mt glioma patients may reflect mutation-driven alterations in cellular, molecular, and spatial heterogeneity which manifest in discernable radiological manifestations.

Purpose To develop a compressed sensing (CS) acceleration method with a high spectral bandwidth exploiting the spatial-spectral sparsity of MR spectroscopic imaging (MRSI). Methods Accelerations were achieved using blip gradients during the readout to perform nonoverlapped and stochastically delayed random walks in kx-ky-t space, combined with block-Hankel matrix completion for efficient reconstruction. Both retrospective and prospective CS accelerations were applied to 13C MRSI experiments, including in vivo rodent brain and liver studies with administrations of hyperpolarized [1-13C] pyruvate at 7.0 Tesla (T) and [2-13C] dihydroxyacetone at 3.0 T, respectively. Results In retrospective undersampling experiments using in vivo 7.0 T data, the proposed method preserved spectral, spatial, and dynamic fidelities with R2 ≥ 0.96 and ≥ 0.87 for pyruvate and lactate signals, respectively, 750-Hz spectral separation, and up to 6.6-fold accelerations. In prospective in vivo experiments, with 3.8-fold acceleration, the proposed method exhibited excellent spatial localization of metabolites and peak recovery for pyruvate and lactate at 7.0 T as well as for dihydroxyacetone and its metabolic products with a 4.5-kHz spectral span (140 ppm at 3.0 T). Conclusions This study demonstrated the feasibility of a new CS approach to accelerate high spectral bandwidth MRSI experiments. Magn Reson Med, 2016. © 2016 Wiley Periodicals, Inc.

Purpose The purpose of this study was to characterize tissue-specific alterations in metabolism of hyperpolarized (HP) gluconeogenic precursors 13 C-lactate and 13 C-pyruvate by rat liver and kidneys under conditions of fasting or insulin-deprived diabetes. Methods Seven normal rats were studied by MR spectroscopic imaging of both HP 13 C-lactate and 13 C-pyruvate in both normal fed and 24 h fasting states, and seven additional rats were scanned after induction of diabetes by streptozotocin (STZ) with insulin withdrawal. Phosphoenolpyruvate carboxykinase (PEPCK) expression levels were also measured in liver and kidney tissues of the STZ-treated rats. Results Multiple sets of significant signal modulations were detected, with graded intensity in general between fasting and diabetic states. An approximate two-fold reduction in the ratio of 13 C-bicarbonate to total 13 C signal was observed in both organs in fasting. The ratio of HP lactate-to-alanine was markedly altered, ranging from a liver-specific 54% increase in fasting, to increases of 69% and 92% in liver and kidney, respectively, in diabetes. Diabetes resulted in a 40% increase in renal lactate signal. STZ resulted in 5.86-fold and 2.73-fold increases in PEPCK expression in liver and kidney, respectively. Conclusion MRI of HP 13 C gluconeogenic precursors may advance diabetes research by clarifying organ-specific roles in abnormal diabetic metabolism. Magn Reson Med 77:1429-1437, 2017. © 2016 International Society for Magnetic Resonance in Medicine.

PURPOSE Dissolution dynamic nuclear polarization (DNP) enables the acquisition of 13 C magnetic resonance data with a high sensitivity. Recently, metabolically inactive hyperpolarized 13 C-labeled compounds have shown to be potentially useful for perfusion imaging. The purpose of this study was to validate hyperpolarized perfusion imaging methods by comparing with conventional gadolinium (Gd)-based perfusion MRI techniques and pathology. METHODS Dynamic 13 C data using metabolically inactive hyperpolarized bis-1,1-(hydroxymethyl)-[1-13 C]cyclopropane-d8 (HMCP) were obtained from an orthotopic human glioblastoma (GBM) model for the characterization of tumor perfusion and compared with standard Gd-based dynamic susceptibility contrast (DSC) MRI data and immunohistochemical analysis from resected brains. RESULTS Distinct HMCP perfusion characteristics were observed within the GBM tumors compared with contralateral normal brain tissue. The perfusion parameters obtained from the hyperpolarized HMCP data in tumor were strongly correlated with normalized peak height measured from the DSC images. The results from immunohistochemical analysis supported these findings by showing a high level of vascular staining for tumor that exhibited high levels of hyperpolarized HMCP signal. CONCLUSION The results from this study have demonstrated that hyperpolarized HMCP data can be used as an indicator of tumor perfusion in an orthotopic xenograft model for GBM. Magn Reson Med 77:841-847, 2017. © 2016 International Society for Magnetic Resonance in Medicine.

Infiltrating low-grade gliomas (LGGs) are a class of terminal central nervous system tumors that comprise malignant neuroglia. Histopathological diagnosis of tumor grade is performed using criteria set by the World Health Organization (WHO) and is based on factors that include nuclear atypia, proliferative capacity, tumor neovascularization, and necrosis.1 The clinical outcome for patients with LGG is variable, with some lesions following a more indolent disease course, while others recur more rapidly and often after undergoing malignant transformation (MT) to a higher grade.2 Lesions that have thus transformed to a grade III anaplastic glioma or grade IV secondary glioblastoma multiforme (GBM) are managed with additional, more aggressive treatments. To date, little is known regarding the nature of recurrent disease, and the most significant prognostic factors for patients diagnosed with LGG are the presence of somatic driver mutations in isocitrate dehydrogenase 1 and 2 (IDH1/2) oncogenes and the codeletion of the 1p and 19q chromosomal arms, which have been associated with increased survival and sensitivity to the treatment given.2–5 IDH mutations have been implicated as an initiating event in gliomagenesis and are key to reprogramming the tumor epigenome and metabolome, largely through neomorphic production and accumulation of 2-hydroxyglutarate.6 Given uncertainties regarding the effectiveness of options available for treating LGGs, IDH mutations have garnered significant attention as a targetable therapeutic pathway, and there are several novel therapies on the horizon.7–9 Until these therapeutics become available, the clinical mainstay of treatment for patients with LGG consists of surgical resection, with radiation therapy and alkylating chemotherapy being typically reserved for recurrences that were either subtotally resected or have undergone MT. MRI is an integral component of brain tumor diagnosis and monitoring. Recent advances in state-of-the-art techniques have enabled the noninvasive assessment of tumor morphology and physiology, with primary GBM having been studied most extensively. Although the ability to noninvasively detect MT would be of significant clinical interest for diagnosis and treatment planning, few studies have focused on addressing this question. Multiparametric MRI holds significant promise for comprehensively characterizing the structural and physiological properties of the tumor. We hypothesize that these advanced imaging techniques may also provide improved characterization of MT in patients with recurrent LGG. The objective of this study was to establish multiparametric MRI profiles of patients with tumors prior to image-guided surgery in order to relate metrics obtained from these methodologies to histopathological grade. Volumetric regions with abnormal imaging features were calculated to provide a robust assessment of the entire recurrent tumor lesion. Regions of viable tumor were targeted for image-guided tissue sampling in order to associate in vivo parameters with histopathological features and to strengthen our understanding of the link between glioma tumor biology and parameters from noninvasive imaging.

PURPOSE: To evaluate the time course and association with survival of anatomic lesion volumes and diffusion imaging parameters for patients with newly diagnosed glioblastoma who were treated with radiation and concurrently with either temozolomide and enzastaurin (TMZ+enza cohort) or temozolomide, erlotonib, and bevaciumab (TMZ+erl+bev cohort). MATERIALS AND METHODS: Regions of interest corresponding to the contrast-enhancing and hyperintense lesions on T2-weighted images were generated. Diffusion-weighted images were processed to provide maps of apparent diffusion coefficient, fractional anisotropy, and longitudinal and radial eigenvalues. Histograms of diffusion values were generated and summary statistics calculated. Cox proportional hazards models were employed to assess the association of representative imaging parameters with survival with adjustments for age, Karnofsky performance status, and extent of resection. RESULTS: Although progression-free survival was significantly longer for the TMZ+erl+bev cohort (12.8 vs 7.3 months), there was no significant difference in overall survival between the two populations (17.0 vs 17.8 months). The median contrast-enhancing lesion volumes decreased from 6.3 to 1.9 cm3 from baseline to the postradiotherapy scan for patients in the TMZ+enza cohort and from 2.8 to 0.9cm3 for the TMZ+erl+bev cohort. Changes in the T2 lesion volumes were only significant for the latter cohort (26.5 to 11.9 cm3). The median apparent diffusion coefficient and related diffusion parameters were significantly increased for the TMZ+enza cohort (1054 to 1225 μm2/s). More of the anatomic parameters were associated with survival for the TMZ+enza cohort, whereas more diffusion parameters were associated with survival for the TMZ+erl+bev cohort. CONCLUSION: The early changes in anatomic and diffusion imaging parameters and their association with survival reflected differences in the mechanisms of action of the treatments that were being given. This suggests that integrating diffusion metrics and anatomic lesion volumes into the Response Assessment in Neuro-Oncology criteria would assist in interpreting treatment-induced changes and predicting outcome in patients with newly diagnosed glioblastoma who are receiving such combination treatments.

Winter is often understudied in ecosystem sciences and viewed as a burden for human systems and infrastructure. However, the importance of winter in regulating ecological processes and shaping human communities has emerged as a topic of great interest, particularly in areas that experience seasonal snow cover. Traditional seasonal definitions may not fully represent below freezing winters and snow accumulation that have historically characterized these areas. Here we: (1) propose the concept of ‘frigid winter’ to address longstanding problems with traditional delineations of winter; and (2) define frigid winter as a period of sustained temperatures below freezing and snow accumulation that together regulate ecological processes and their services. We explore this definition and the changes occurring within it using 100 years of meteorological data from northeastern North America. Trend analysis demonstrates that frigid winters have shortened by ∼3 weeks over the last century, that cold, snowy conditions have become more intermittent, and that the choice of winter delineation (astronomical, meteorological, hibernal, or frigid) influences the apparent rate at which winter conditions disappear.

Noninvasive tools that target tumor cells could improve the management of glioma. Cancer generally has a high demand for Fe(III), an essential nutrient for a variety of biochemical processes. We tested whether 68Ga-citrate, an Fe(III) biomimetic that binds to apo-transferrin in blood, detects glioma in preclinical models and patients using hybrid PET/MRI. Mouse PET/CT studies showed that 68Ga-citrate accumulates in subcutaneous U87MG xenografts in a transferrin receptor-dependent fashion within 4 hours after injection. Seventeen patients with WHO grade III or IV glioma received 3.7-10.2 mCi 68Ga-citrate and were imaged with PET/MR 123-307 minutes after injection to establish that the radiotracer can localize to human tumors. Multiple contrast-enhancing lesions were PET avid, and tumor to adjacent normal white matter ratios were consistently greater than 10:1. Several contrast-enhancing lesions were not PET avid. One minimally enhancing lesion and another tumor with significantly reduced enhancement following bevacizumab therapy were PET avid. Advanced MR imaging analysis of one patient with contrast-enhancing glioblastoma showed that metabolic hallmarks of viable tumor spatially overlaid with 68Ga-citrate accumulation. These early data underscore that high-grade glioma may be detectable with a radiotracer that targets Fe(III) transport.

Recurrent high grade gliomas (rHGG) are difficult to diagnose accurately as they are often confounded with treatment-induced effects (TxE) because on conventional T1w and T2w anatomical MR imaging these two phenomena appear identical. This could result in removing a patient from an effective second-line therapy, confound the results of a clinical trial of a new therapeutic, and expose a patient to unnecessary surgical intervention. Advanced MR imaging modalities have shown promise in distinguishing between TxE and rHGG, but prior studies are unable to account for heterogeneity within the same lesion and often lack pathological confirmation. The goal of this study was to identify imaging parameters that could spatially map directly to pathology to account for heterogeneity within lesions. 1–8 tissue samples were collected upon surgical resection of suspected rHGG. A total of 484 samples were collected from 183 patients; 332 of these (163 patients) were labeled as either pathologically confirmed treatment effect or having no tumor cells (tumor score=0) within the imaging abnormality (TxE; 80/51 samples/patients) or rHGG (tumor score=2–3; 252/118 samples/patients) by a pathologist. Preoperative 3T MRI scans included T1w-Gd and T2w FLAIR; diffusion tensor imaging (b=1000s/mm2); 3D MRSI; and dynamic susceptibility-contrast perfusion MRI. Univariate models were created using generalized estimating equations to evaluate each variable’s ability to distinguish TxE from rHGG tissue samples. Normalized choline (median=1.1 TxE & 1.2 rHGG), choline-to-NAA index (CNI, median=2.4 TxE & 3.5 rHGG), and normalized cerebral blood volume (nCBV, median=1.2 TxE & 1.4 rHGG) were significantly associated with biopsy-level classification (p=0.034, 0.015, 0.017). These results are being consolidated into a multiparametric algorithm for predicting TxE or rHGG, which could be of clinical importance in managing patients with recurrent rHGG. Downstream analysis will create a spatial map of rHGG to help guide future surgical sampling.

Although the overall prognostic significance of maximal surgical resection of contrast-enhancing tumor in glioblastoma patients is well established, prior studies have not evaluated the combined importance of resection, molecular markers, patient characteristics, and chemoradiation. Incorporation of these factors may redefine the relative benefit of cytoreductive surgery and establish differing thresholds for extent of resection in varying clinical presentations. In the first study of its kind, we examine the interactive effects of volumetric extent of resection with molecular and clinical factors to develop a new roadmap for cytoreductive surgery. Based on a 20-year retrospective cohort of 850 glioblastoma patients who had initial surgery at UCSF, we employed survival models and recursive partitioning (RPA) to investigate multivariate relationships of overall survival (OS), both in the entire cohort as well as a subset diagnosed since 2005 (Stupp-era) with IDH1 mutation status available (n=470). For the entire cohort and the Stupp-era subset, the RPAs elucidate the combinatorial consequence of treatment, age, IDH1 status (in the subset), and resection of both enhancing and non-enhancing tumor. In the Stupp-era, temozolomide-treated patients that are IDH-wildtype and >65 clearly benefit from a reduction of the enhancing tumor (median OS: 10.1 vs 15.8 months). IDH-wildtype, temozolomide-treated patients under 65 benefit from reduction of both enhancing and non-enhancing tumor with a median survival similar to that of IDH-mutant, temozolomide-treated patients (combined median OS: 33.7 months). The patients faring worst are those that did not receive temozolomide that are >65 and/or have ≥0.3 cm(3) residual enhancing tumor (median OS: 4 months). These risk models outperform all published prognostic models. This is the first study to combine resection of contrast-enhancing and non-enhancing tumor in conjunction with molecular and clinical information in a large single-institution study, and paves the way for rethinking surgical strategies for individual patients with newly diagnosed glioblastoma.