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.

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.

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.

Correcting B 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.

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.

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.

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.

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 (CMRO) 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 CMRO 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 R*; VSEAN to estimate baseline O extraction fraction (OEF) from a measurement of venous blood R, which in combination with the baseline CBF measurement yields an estimate of baseline CMRO; and FLAIR-GESSE to measure tissue R' to estimate the scaling parameter needed for calculating the change in CMRO in response to a stimulus with the calibrated BOLD method.

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.

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.

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.

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.

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.

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.

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.

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.