The potential for gas-free measurements of absolute oxygen metabolism during both baseline and activation states in the human brain.

Quantitative functional magnetic resonance imaging methods make it possible to measure cerebral oxygen metabolism (CMRO2) in the human brain. Current methods require the subject to breathe special gas mixtures (hypercapnia and hyperoxia). We tested a noninvasive suite of methods to measure absolute CMRO2 in both baseline and dynamic activation states without the use of special gases: arterial spin labeling (ASL) to measure baseline and activation cerebral blood flow (CBF), with concurrent measurement of the blood oxygenation level dependent (BOLD) signal as a dynamic change in tissue R2*; VSEAN to estimate baseline O2 extraction fraction (OEF) from a measurement of venous blood R2, which in combination with the baseline CBF measurement yields an estimate of baseline CMRO2; and FLAIR-GESSE to measure tissue R2' to estimate the scaling parameter needed for calculating the change in CMRO2 in response to a stimulus with the calibrated BOLD method. Here we describe results for a study sample of 17 subjects (8 female, mean age = 25.3 years, range 21-31 years). The primary findings were that OEF values measured with the VSEAN method were in good agreement with previous PET findings, while estimates of the dynamic change in CMRO2 in response to a visual stimulus were in good agreement between the traditional hypercapnia calibration and calibration based on R2'. These results support the potential of gas-free methods for quantitative physiological measurements.

A novel Bayesian approach to accounting for uncertainty in fMRI-derived estimates of cerebral oxygen metabolism fluctuations.

Calibrated blood oxygenation level dependent (BOLD) imaging is a multimodal functional MRI technique designed to estimate changes in cerebral oxygen metabolism from measured changes in cerebral blood flow and the BOLD signal. This technique addresses fundamental ambiguities associated with quantitative BOLD signal analysis; however, its dependence on biophysical modeling creates uncertainty in the resulting oxygen metabolism estimates. In this work, we developed a Bayesian approach to estimating the oxygen metabolism response to a neural stimulus and used it to examine the uncertainty that arises in calibrated BOLD estimation due to the presence of unmeasured model parameters. We applied our approach to estimate the CMRO2 response to a visual task using the traditional hypercapnia calibration experiment as well as to estimate the metabolic response to both a visual task and hypercapnia using the measurement of baseline apparent R2' as a calibration technique. Further, in order to examine the effects of cerebral spinal fluid (CSF) signal contamination on the measurement of apparent R2', we examined the effects of measuring this parameter with and without CSF-nulling. We found that the two calibration techniques provided consistent estimates of the metabolic response on average, with a median R2'-based estimate of the metabolic response to CO2 of 1.4%, and R2'- and hypercapnia-calibrated estimates of the visual response of 27% and 24%, respectively. However, these estimates were sensitive to different sources of estimation uncertainty. The R2'-calibrated estimate was highly sensitive to CSF contamination and to uncertainty in unmeasured model parameters describing flow-volume coupling, capillary bed characteristics, and the iso-susceptibility saturation of blood. The hypercapnia-calibrated estimate was relatively insensitive to these parameters but highly sensitive to the assumed metabolic response to CO2.

Understanding the dynamic relationship between cerebral blood flow and the BOLD signal: Implications for quantitative functional MRI.

Calibrated BOLD imaging, in which traditional measurements of the BOLD signal are combined with measurements of cerebral blood flow (CBF) within a BOLD biophysical model to estimate changes in oxygen metabolism (CMRO2), has been a valuable tool for untangling the physiological processes associated with neural stimulus-induced BOLD activation. However, to date this technique has largely been applied to the study of essentially steady-state physiological changes (baseline to activation) associated with block-design stimuli, and it is unclear whether this approach may be directly extended to the study of more dynamic, naturalistic experimental designs. In this study we tested an assumption underlying this technique whose validity is critical to the application of calibrated BOLD to the study of more dynamic stimuli, that information about fluctuations in venous cerebral blood volume (CBVv) can be captured indirectly by measuring fluctuations in CBF, making the independent measurement of CBVv unnecessary. To accomplish this, simultaneous arterial spin labeling and BOLD imaging were used to measure the CBF and BOLD responses to flickering checkerboards with contrasts that oscillated continuously with frequencies of ~0.02-0.16Hz. The measurements were then fit to a dynamic physiological model of the BOLD response in order to explore the range of consistent CMRO2 and CBVv responses. We found that the BOLD and CBF responses were most consistent with relatively tight dynamic coupling between CBF and CMRO2 and a CBVv response that was an order of magnitude slower than either CBF or CMRO2. This finding suggests that the assumption of tight flow-volume coupling may not be strictly valid, complicating the extension of calibrated BOLD to more naturalistic experimental designs.

The coupling of cerebral blood flow and oxygen metabolism with brain activation is similar for simple and complex stimuli in human primary visual cortex.

Quantitative functional MRI (fMRI) experiments to measure blood flow and oxygen metabolism coupling in the brain typically rely on simple repetitive stimuli. Here we compared such stimuli with a more naturalistic stimulus. Previous work on the primary visual cortex showed that direct attentional modulation evokes a blood flow (CBF) response with a relatively large oxygen metabolism (CMRO2) response in comparison to an unattended stimulus, which evokes a much smaller metabolic response relative to the flow response. We hypothesized that a similar effect would be associated with a more engaging stimulus, and tested this by measuring the primary human visual cortex response to two contrast levels of a radial flickering checkerboard in comparison to the response to free viewing of brief movie clips. We did not find a significant difference in the blood flow-metabolism coupling (n=%ΔCBF/%ΔCMRO2) between the movie stimulus and the flickering checkerboards employing two different analysis methods: a standard analysis using the Davis model and a new analysis using a heuristic model dependent only on measured quantities. This finding suggests that in the primary visual cortex a naturalistic stimulus (in comparison to a simple repetitive stimulus) is either not sufficient to provoke a change in flow-metabolism coupling by attentional modulation as hypothesized, that the experimental design disrupted the cognitive processes underlying the response to a more natural stimulus, or that the technique used is not sensitive enough to detect a small difference.

Calibrating the BOLD response without administering gases: comparison of hypercapnia calibration with calibration using an asymmetric spin echo.

The calibrated BOLD (blood oxygen level dependent) technique was developed to quantify the BOLD signal in terms of changes in oxygen metabolism. In order to achieve this a calibration experiment must be performed, which typically requires a hypercapnic gas mixture to be administered to the participant. However, an emerging technique seeks to perform this calibration without administering gases using a refocussing based calibration. Whilst hypercapnia calibration seeks to emulate the physical removal of deoxyhaemoglobin from the blood, the aim of refocussing based calibration is to refocus the dephasing effect of deoxyhaemoglobin on the MR signal using a spin echo. However, it is not possible to refocus all of the effects that contribute to the BOLD signal and a scale factor is required to estimate the BOLD scaling parameter M. In this study the feasibility of a refocussing based calibration was investigated. The scale factor relating the refocussing calibration to M was predicted by simulations to be approximately linear and empirically measured to be 0.88±0.36 for the visual cortex and 0.93±0.32 for a grey matter region of interest (mean±standard deviation). Refocussing based calibration is a promising approach for greatly simplifying the calibrated BOLD methodology by eliminating the need for the subject to breathe special gas mixtures, and potentially provides the basis for a wider implementation of quantitative functional MRI.

Integrating Overall Survival and Tumor Control Probability Models to Predict Local Progression After Brain Metastasis Radiosurgery.

Purpose: Stereotactic radiosurgery (SRS) for brain metastases is frequently prescribed to the maximum tolerated dose to minimize the probability of local progression. However, many patients die from extracranial disease prior to local progression and may not require maximally aggressive treatment. Recently, improvements in models of SRS tumor control probability (TCP) and overall survival (OS) have been made. We predicted that by combining models of OS and TCP, we could better predict the true risk of local progression after SRS than by using TCP modeling alone. Methods and Materials: Records of patients undergoing SRS at a single institution were reviewed retrospectively. Using established TCP and OS models, for each patient, the probability of 1-year survival [p(OS)] was calculated, as was the probability of 1-year local progression [p(LP)]) for each treated lesion. Joint-probability was used to combine the models [p(LP,OS)=p(LP)*p(OS)]. Analyses were conducted at the individual metastasis and whole-patient levels. Fine-Gray regression was used to model p(LP) or p(LP,OS) on the risk of local progression after SRS, with death as a competing risk. Results: At the patient level, 1-year local progression was 0.08 (95% CI, 0.03-0.15), median p(LP,OS) was 0.13 (95% CI, 0.07-0.2), and median p(LP) was 0.29 (95% CI, 0.22-0.38). At the metastasis level, 1-year local progression was 0.02 (95% CI, 0.01-0.04), median p(LP,OS) was 0.05 (95% CI, 0.02-0.07), and median p(LP) was 0.10 (95% CI, 0.07-0.13). p(LP,OS) was found to be significantly associated with the risk of local progression at the patient level (P = .048) and metastasis level (P = .007); however, p(LP) was not (P = .16 and P = .28, respectively). Conclusions: Simultaneous modeling of OS and TCP more accurately predicted local progression than TCP modeling alone. Better understanding which patients with brain metastases are at risk of local progression after SRS may help personalize treatment to minimize risk without sacrificing efficacy.

A review of calibrated blood oxygenation level-dependent (BOLD) methods for the measurement of task-induced changes in brain oxygen metabolism.

The dynamics of the blood oxygenation level-dependent (BOLD) response are dependent on changes in cerebral blood flow, cerebral blood volume and the cerebral metabolic rate of oxygen consumption. Furthermore, the amplitude of the response is dependent on the baseline physiological state, defined by the haematocrit, oxygen extraction fraction and cerebral blood volume. As a result of this complex dependence, the accurate interpretation of BOLD data and robust intersubject comparisons when the baseline physiology is varied are difficult. The calibrated BOLD technique was developed to address these issues. However, the methodology is complex and its full promise has not yet been realised. In this review, the theoretical underpinnings of calibrated BOLD, and issues regarding this theory that are still to be resolved, are discussed. Important aspects of practical implementation are reviewed and reported applications of this methodology are presented.

Automated segmentation of multiparametric magnetic resonance images for cerebral AVM radiosurgery planning: a deep learning approach.

Stereotactic radiosurgery planning for cerebral arteriovenous malformations (AVM) is complicated by the variability in appearance of an AVM nidus across different imaging modalities. We developed a deep learning approach to automatically segment cerebrovascular-anatomical maps from multiple high-resolution magnetic resonance imaging/angiography (MRI/MRA) sequences in AVM patients, with the goal of facilitating target delineation. Twenty-three AVM patients who were evaluated for radiosurgery and underwent multi-parametric MRI/MRA were included. A hybrid semi-automated and manual approach was used to label MRI/MRAs with arteries, veins, brain parenchyma, cerebral spinal fluid (CSF), and embolized vessels. Next, these labels were used to train a convolutional neural network to perform this task. Imaging from 17 patients (6362 image slices) was used for training, and 6 patients (1224 slices) for validation. Performance was evaluated by Dice Similarity Coefficient (DSC). Classification performance was good for arteries, veins, brain parenchyma, and CSF, with DSCs of 0.86, 0.91, 0.98, and 0.91, respectively in the validation image set. Performance was lower for embolized vessels, with a DSC of 0.75. This demonstrates the proof of principle that accurate, high-resolution cerebrovascular-anatomical maps can be generated from multiparametric MRI/MRA. Clinical validation of their utility in radiosurgery planning is warranted.

Correcting B0 inhomogeneity-induced distortions in whole-body diffusion MRI of bone.

Diffusion-weighted magnetic resonance imaging (DWI) of the musculoskeletal system has various applications, including visualization of bone tumors. However, DWI acquired with echo-planar imaging is susceptible to distortions due to static magnetic field inhomogeneities. This study aimed to estimate spatial displacements of bone and to examine whether distortion corrected DWI images more accurately reflect underlying anatomy. Whole-body MRI data from 127 prostate cancer patients were analyzed. The reverse polarity gradient (RPG) technique was applied to DWI data to estimate voxel-level distortions and to produce a distortion corrected DWI dataset. First, an anatomic landmark analysis was conducted, in which corresponding vertebral landmarks on DWI and anatomic T2-weighted images were annotated. Changes in distance between DWI- and T2-defined landmarks (i.e., changes in error) after distortion correction were calculated. In secondary analyses, distortion estimates from RPG were used to assess spatial displacements of bone metastases. Lastly, changes in mutual information between DWI and T2-weighted images of bone metastases after distortion correction were calculated. Distortion correction reduced anatomic error of vertebral DWI up to 29 mm. Error reductions were consistent across subjects (Wilcoxon signed-rank p < 10-20). On average (± SD), participants' largest error reduction was 11.8 mm (± 3.6). Mean (95% CI) displacement of bone lesions was 6.0 mm (95% CI 5.0-7.2); maximum displacement was 17.1 mm. Corrected diffusion images were more similar to structural MRI, as evidenced by consistent increases in mutual information (Wilcoxon signed-rank p < 10-12). These findings support the use of distortion correction techniques to improve localization of bone on DWI.

Lymphatic-preserving treatment sequencing with immune checkpoint inhibition unleashes cDC1-dependent antitumor immunity in HNSCC.

Despite the promise of immune checkpoint inhibition (ICI), therapeutic responses remain limited. This raises the possibility that standard of care treatments delivered in concert may compromise the tumor response. To address this, we employ tobacco-signature head and neck squamous cell carcinoma murine models in which we map tumor-draining lymphatics and develop models for regional lymphablation with surgery or radiation. We find that lymphablation eliminates the tumor ICI response, worsening overall survival and repolarizing the tumor- and peripheral-immune compartments. Mechanistically, within tumor-draining lymphatics, we observe an upregulation of conventional type I dendritic cells and type I interferon signaling and show that both are necessary for the ICI response and lost with lymphablation. Ultimately, we provide a mechanistic understanding of how standard oncologic therapies targeting regional lymphatics impact the tumor response to immune-oncology therapy in order to define rational, lymphatic-preserving treatment sequences that mobilize systemic antitumor immunity, achieve optimal tumor responses, control regional metastatic disease, and confer durable antitumor immunity.

Defining the Role of Immunotherapy in the Curative Treatment of Locoregionally Advanced Head and Neck Cancer: Promises, Challenges, and Opportunities.

Recent advancements in the development of immunotherapies have raised the hope for patients with locally-advanced HNSCC (LA-HNSCC) to achieve improved oncologic outcomes without the heavy burden of treatment-related morbidity. While there are several ongoing late phase clinical trials that seek to determine whether immunotherapy can be effectively employed in the definitive setting, initial results from concurrent immuno-radiotherapy therapy trials have not shown strong evidence of benefit. Encouragingly, evidence from preclinical studies and early-phase neoadjuvant studies have begun to show potential pathways forward, with therapeutic combinations and sequences that intentionally spare tumor draining lymphatics in order to maximize the synergy between definitive local therapy and immunotherapy. The intent of this review is to summarize the scientific rationale and current clinical evidence for employing immunotherapy for LA-HNSCC as well as the ongoing efforts and challenges to determine how to optimally deliver and sequence immunotherapy alongside traditional therapeutics. In both the preclinical and clinical settings, we will discuss the application of immunotherapies to both surgical and radiotherapeutic management of HNSCC.

Microstructural Injury to Corpus Callosum and Intrahemispheric White Matter Tracts Correlate With Attention and Processing Speed Decline After Brain Radiation.

PURPOSE: The corpus callosum (CC) and intrahemispheric white matter tracts (IHWM) subserve critical aspects of attention and processing speed. We analyzed imaging biomarkers of microstructural injury within these regions and association with attention and processing speed performance before and after radiation therapy in primary brain tumor patients. METHODS AND MATERIALS: In a prospective clinical trial, 44 primary brain tumor patients underwent cognitive testing and magnetic resonance imaging/diffusion-weighted imaging at baseline (pre-radiation therapy) and 3-, 6-, and 12-months post-radiation therapy. CC (subregions, total) and IHWM tracts (left/right without CC, total) were autosegmented; tumor, tumor bed, and edema were censored. Biomarkers included volume changes (cm3), mean diffusivity ([MD]; higher values indicate white matter injury), fractional anisotropy ([FA]; lower values indicate white matter injury). Reliable-change indices measured changes in attention (Weschler Adult Intelligence Scale [WAIS-IV] digits-forward; Delis-Kaplan Executive Function System Trail Making [D-KEFS-TM] visual-scanning), and processing speed (WAIS-IV coding; D-KEFS-TM number-sequencing, letter-sequencing), accounting for practice effects. Linear mixed-effects models evaluated associations between mean radiation dose and biomarkers (volume, MD, FA) and imaging biomarkers and neurocognitive performance. Statistics were corrected for multiple comparisons. RESULTS: Processing speed declined at 6 months following radiation therapy (number sequencing, letter sequencing; P < .04). Seizures and antiepileptic drug therapy were associated with lower visual-scanning attention reliable-change indices at 6 months (P = .039). Higher radiation dose correlated with smaller midanterior CC volume (P = .023); lower FA in posterior CC, anterior CC, and total CC (all P < .03); and higher MD in anterior CC (P = .012). Smaller midanterior CC and left IHWM volume correlated with worse processing speed (coding, letter-sequencing, number-sequencing; all P < .03). Higher FA in right, left, and total IHWM correlated with better coding scores (all P < .01). Lower FA in total IHWM (P = .009) was associated with worse visual-scanning attention scores. Higher FA in midposterior CC (P = .029) correlated with better digits-forward attention scores. CONCLUSIONS: The CC demonstrated radiation dose-dependent atrophy and WM injury. Microstructural injury within the CC and IHWM was associated with attention and processing speed decline after radiation therapy. These areas represent possible avoidance regions for preservation of attention and processing speed.

Implementation of peer-review quality rounds for gynecologic brachytherapy in a high-volume academic center.

PURPOSE: While peer review is critical for quality and safety in radiotherapy, there are neither formal guidelines nor format examples for brachytherapy (BT) peer review. We report on a gynecologic BT peer-review method implemented at a high-volume academic center. METHODS AND MATERIALS: We analyzed discussions at bimonthly gynecologic BT peer-review rounds between July and December 2018. Rounds consisted of 2-5 attending physicians with gynecologic BT expertise, 1-2 BT physicists, and trainees. Peer-review targets included clinical case review, contours, implant technique, dose/fractionation, and target/organ-at-risk (OAR) dosimetry. The projected/final target and OAR dosimetry were analyzed. RESULTS: 55 separate implants from 44 patients were reviewed. Implants were mostly reviewed after the first BT fraction (n = 16, 29%) or at another time point during BT (n = 20, 36%). One (2%) implant was presented prospectively. The applicator type and BT technique were reviewed for all implants. Dose/fractionation was evaluated for 46 implants (84%); contours were discussed for 21 (38%). Target and OAR dosimetry were reviewed for 54 (98%) and 28 implants (51%), respectively. Six cases (11%) underwent minor changes to the applicator type to improve target and/or OAR dosimetry. One case (2%) had a major change recommended to the dose/fractionation. CONCLUSIONS: Gynecologic BT peer review may enhance BT quality by allowing for implant optimization and formal review of challenging cases, ultimately improving medical decision-making and team communication. Peer review should be implemented in centers offering gynecologic BT.

Variability of the coupling of blood flow and oxygen metabolism responses in the brain: a problem for interpreting BOLD studies but potentially a new window on the underlying neural activity.

Recent studies from our group and others using quantitative fMRI methods have found that variations of the coupling ratio of blood flow (CBF) and oxygen metabolism (CMRO2) responses to a stimulus have a strong effect on the BOLD response. Across a number of studies an empirical pattern is emerging in the way CBF and CMRO2 changes are coupled to neural activation: if the stimulus is modulated to create a stronger response (e.g., increasing stimulus contrast), CBF is modulated more than CMRO2; on the other hand, if the brain state is altered such that the response to the same stimulus is increased (e.g., modulating attention, adaptation, or excitability), CMRO2 is modulated more than CBF. Because CBF and CMRO2 changes conflict in producing BOLD signal changes, this finding has an important implication for conventional BOLD-fMRI studies: the BOLD response exaggerates the effects of stimulus variation but is only weakly sensitive to modulations of the brain state that alter the response to a standard stimulus. A speculative hypothesis is that variability of the coupling ratio of the CBF and CMRO2 responses reflects different proportions of inhibitory and excitatory evoked activity, potentially providing a new window on neural activity in the human brain.

A novel method of combining blood oxygenation and blood flow sensitive magnetic resonance imaging techniques to measure the cerebral blood flow and oxygen metabolism responses to an unknown neural stimulus.

Simultaneous implementation of magnetic resonance imaging methods for Arterial Spin Labeling (ASL) and Blood Oxygenation Level Dependent (BOLD) imaging makes it possible to quantitatively measure the changes in cerebral blood flow (CBF) and cerebral oxygen metabolism (CMRO(2)) that occur in response to neural stimuli. To date, however, the range of neural stimuli amenable to quantitative analysis is limited to those that may be presented in a simple block or event related design such that measurements may be repeated and averaged to improve precision. Here we examined the feasibility of using the relationship between cerebral blood flow and the BOLD signal to improve dynamic estimates of blood flow fluctuations as well as to estimate metabolic-hemodynamic coupling under conditions where a stimulus pattern is unknown. We found that by combining the information contained in simultaneously acquired BOLD and ASL signals through a method we term BOLD Constrained Perfusion (BCP) estimation, we could significantly improve the precision of our estimates of the hemodynamic response to a visual stimulus and, under the conditions of a calibrated BOLD experiment, accurately determine the ratio of the oxygen metabolic response to the hemodynamic response. Importantly we were able to accomplish this without utilizing a priori knowledge of the temporal nature of the neural stimulus, suggesting that BOLD Constrained Perfusion estimation may make it feasible to quantitatively study the cerebral metabolic and hemodynamic responses to more natural stimuli that cannot be easily repeated or averaged.

A New Functional MRI Approach for Investigating Modulations of Brain Oxygen Metabolism.

Functional MRI (fMRI) using the blood oxygenation level dependent (BOLD) signal is a common technique in the study of brain function. The BOLD signal is sensitive to the complex interaction of physiological changes including cerebral blood flow (CBF), cerebral blood volume (CBV), and cerebral oxygen metabolism (CMRO2). A primary goal of quantitative fMRI methods is to combine BOLD imaging with other measurements (such as CBF measured with arterial spin labeling) to derive information about CMRO2. This requires an accurate mathematical model to relate the BOLD signal to the physiological and hemodynamic changes; the most commonly used of these is the Davis model. Here, we propose a new nonlinear model that is straightforward and shows heuristic value in clearly relating the BOLD signal to blood flow, blood volume and the blood flow-oxygen metabolism coupling ratio. The model was tested for accuracy against a more detailed model adapted for magnetic fields of 1.5, 3 and 7T. The mathematical form of the heuristic model suggests a new ratio method for comparing combined BOLD and CBF data from two different stimulus responses to determine whether CBF and CMRO2 coupling differs. The method does not require a calibration experiment or knowledge of parameter values as long as the exponential parameter describing the CBF-CBV relationship remains constant between stimuli. The method was found to work well for 1.5 and 3T but is prone to systematic error at 7T. If more specific information regarding changes in CMRO2 is required, then with accuracy similar to that of the Davis model, the heuristic model can be applied to calibrated BOLD data at 1.5T, 3T and 7T. Both models work well over a reasonable range of blood flow and oxygen metabolism changes but are less accurate when applied to a simulated caffeine experiment in which CBF decreases and CMRO2 increases.