Seizure outcomes following single-fraction versus hypofractionated radiosurgery for brain metastases: a single-center experience.

OBJECTIVE: Although seizures are a relatively common phenomenon in the setting of brain metastases (BMs), there are no discrete recommendations regarding the use of antiepileptic drugs (AEDs) in this population, either in general or in the context of treatment. The authors' aim was to better understand the underlying pathological factors as well as the therapeutic techniques that may lead to seizures following the radiosurgical treatment of BMs with the goal of guiding appropriate AED prophylaxis. METHODS: Adult patients with BMs diagnosed from 2013 to 2020 at a single academic institution and treated with radiation therapy were included in this study. The authors evaluated factors associated with the incidence of seizures throughout the disease course, with a focus on seizures in the 90-day period following stereotactic radiosurgery (SRS). RESULTS: Four hundred forty-four patients with newly diagnosed BMs were identified, 10% of whom had seizures at the time of presentation and 28% of whom had a seizure at any point during the study period. Tumor histology was significantly associated with initial seizure risk. AED use was highly variable. In the 90-day post-SRS period, the summed total planning target volume (PTV) was independently predictive of post-SRS seizures, regardless of the fractionation scheme (single fraction vs hypofractionated) and other clinical factors. The number of supratentorial BMs was not predictive of post-SRS seizures. CONCLUSIONS: PTV is a superior predictor of post-SRS seizures relative to the number of supratentorial BMs, as it serves as a volumetric proxy for intracranial disease burden. A larger PTV, alongside tumor histology and prior seizure history, should be considered in the decision-making process for AED use following radiosurgery.

A survival prediction model via interpretable machine learning for patients with oropharyngeal cancer following radiotherapy.

PURPOSE: To explore interpretable machine learning (ML) methods, with the hope of adding more prognosis value, for predicting survival for patients with Oropharyngeal-Cancer (OPC). METHODS: A cohort of 427 OPC patients (Training 341, Test 86) from TCIA database was analyzed. Radiomic features of gross-tumor-volume (GTV) extracted from planning CT using Pyradiomics, and HPV p16 status, etc. patient characteristics were considered as potential predictors. A multi-level dimension reduction algorithm consisting of Least-Absolute-Selection-Operator (Lasso) and Sequential-Floating-Backward-Selection (SFBS) was proposed to effectively remove redundant/irrelevant features. The interpretable model was constructed by quantifying the contribution of each feature to the Extreme-Gradient-Boosting (XGBoost) decision by Shapley-Additive-exPlanations (SHAP) algorithm. RESULTS: The Lasso-SFBS algorithm proposed in this study finally selected 14 features, and our prediction model achieved an area-under-ROC-curve (AUC) of 0.85 on the test dataset based on this feature set. The ranking of the contribution values calculated by SHAP shows that the top predictors that were most correlated with survival were ECOG performance status, wavelet-LLH_firstorder_Mean, chemotherapy, wavelet-LHL_glcm_InverseVariance, tumor size. Those patients who had chemotherapy, with positive HPV p16 status, and lower ECOG performance status, tended to have higher SHAP scores and longer survival; who had an older age at diagnosis, heavy drinking and smoking pack year history, tended to lower SHAP scores and shorter survival. CONCLUSION: We demonstrated predictive values of combined patient characteristics and imaging features for the overall survival of OPC patients. The multi-level dimension reduction algorithm can reliably identify the most plausible predictors that are mostly associated with overall survival. The interpretable patient-specific survival prediction model, capturing correlations of each predictor and clinical outcome, was developed to facilitate clinical decision-making for personalized treatment.

Automated Tumor Segmentation in Radiotherapy.

Autosegmentation of gross tumor volumes holds promise to decrease clinical demand and to provide consistency across clinicians and institutions for radiation treatment planning. Additionally, autosegmentation can enable imaging analyses such as radiomics to construct and deploy large studies with thousands of patients. Here, we review modern results that utilize deep learning approaches to segment tumors in 5 major clinical sites: brain, head and neck, thorax, abdomen, and pelvis. We focus on approaches that inch closer to clinical adoption, highlighting winning entries in international competitions, unique network architectures, and novel ways of overcoming specific challenges. We also broadly discuss the future of gross tumor volumes autosegmentation and the remaining barriers that must be overcome before widespread replacement or augmentation of manual contouring.

Relapse patterns and radiation dose exposure in IDH wild-type glioblastoma at first radiographic recurrence following chemoradiation.

PURPOSE: To quantify the radiation dose distribution and lesion morphometry (shape) at baseline, prior to chemoradiation, and at the time of radiographic recurrence in patients with glioblastoma (GBM). METHODS: The IMRT dose distribution, location of the center of mass, sphericity, and solidity of the contrast enhancing tumor at baseline and the time of tumor recurrence was quantified in 48 IDH wild-type GBM who underwent postoperative IMRT (2 Gy daily for total of 60 Gy) with concomitant and adjuvant temozolomide. RESULTS: Average radiation dose within enhancing tumor at baseline and recurrence was ≥ 60 Gy. Centroid location of the enhancing tumor shifted an average of 11.3 mm at the time of recurrence with respect to pre-IMRT location. A positive correlation was observed between change in centroid location and PFS in MGMT methylated patients (P = 0.0007) and Cox multivariate regression confirmed centroid distance from baseline was associated with PFS when accounting for clinical factors (P = 0.0189). Lesion solidity was higher at recurrence compared to baseline (P = 0.0118). Tumors that progressed > 12 weeks after IMRT were significantly more spherical (P = 0.0094). CONCLUSION: Most GBMs recur local within therapeutic IMRT doses; however, tumors with longer PFS occurred further from the original tumor location and were more solid and/or nodular.

Urethral Interfractional Geometric and Dosimetric Variations of Prostate Cancer Patients: A Study Using an Onboard MRI.

Purpose: For a cohort of prostate cancer patients treated on an MR-guided radiotherapy (MRgRT) system, we retrospectively analyzed urethral interfractional geometric and dosimetric variations based on onboard MRIs acquired at different timepoints and evaluated onboard prostatic urethra visualization for urethra-focused online adaptive RT. Methods: Twenty-six prostate cancer patients were prospectively scanned on a 0.35-T MRgRT system using an optimized T2-weighted HASTE sequence at simulation and final fraction. Two radiation oncologists (RO1 and RO2) contoured the urethras on all HASTE images. The simulation and final fraction HASTE images were rigidly registered, and urethral interobserver and interfractional geometric variation was evaluated using the 95th percentile Hausdorff distance (HD95), mean distance to agreement (MDA), center-of-mass shift (COMS), and DICE coefficient. For dosimetric analysis, simulation and final fraction HASTE images were registered to the 3D bSSFP planning MRI and 3D bSSFP final setup MRI, respectively. Both ROs' urethra contours were transferred from HASTE images for initial treatment plan optimization and final fraction dose estimation separately. Stereotactic body radiotherapy (SBRT) plans, 40 Gy in 5 fractions, were optimized to meet clinical constraints, including urethral V42Gy ≤0.03 cc, on the planning MRI. The initial plan was then forward calculated on the final setup MRI to estimate urethral dose on the final fraction and evaluate urethral dosimetric impact due to anatomy change. Results: The average interobserver HD95, MDA, COMS, and DICE were 2.85 ± 1.34 mm, 1.02 ± 0.36 mm, 3.16 ± 1.61 mm, and 0.58 ± 0.15, respectively. The average interfractional HD95, MDA, COMS, and DICE were 3.26 ± 1.54 mm, 1.29 ± 0.54 mm, 3.34 ± 2.01 mm, and 0.49 ± 0.18, respectively. All patient simulation MRgRT plans met all clinical constraints. For RO1 and RO2, 23/26 (88%) and 21/26 (81%) patients' final fraction estimated urethral dose did not meet the planned constraint. The average urethral V42Gy change was 0.48 ± 0.58 cc. Conclusion: Urethral interfractional motion and anatomic change can result in daily treatment violating urethral constraints. Onboard MRI with good visualization of the prostatic urethra can be a valuable tool to help better protect the urethra through patient setup or online adaptive RT.

Evaluation of T2-Weighted MRI for Visualization and Sparing of Urethra with MR-Guided Radiation Therapy (MRgRT) On-Board MRI.

PURPOSE: To evaluate urethral contours from two optimized urethral MRI sequences with an MR-guided radiotherapy system (MRgRT). METHODS: Eleven prostate cancer patients were scanned on a MRgRT system using optimized urethral 3D HASTE and 3D TSE. A resident radiation oncologist contoured the prostatic urethra on the patients' planning CT, diagnostic 3T T2w MRI, and both urethral MRIs. An attending radiation oncologist reviewed/edited the resident's contours and additionally contoured the prostatic urethra on the clinical planning MRgRT MRI (bSSFP). For each image, the resident radiation oncologist, attending radiation oncologist, and a senior medical physicist qualitatively scored the prostatic urethra visibility. Using MRgRT 3D HASTE-based contouring workflow as baseline, prostatic urethra contours drawn on CT, diagnostic MRI, clinical bSSFP and 3D TSE were evaluated relative to the contour on 3D HASTE using 95th percentile Hausdorff distance (HD95), mean-distance-to-agreement (MDA), and DICE coefficient. Additionally, prostatic urethra contrast-to-noise-ratios (CNR) were calculated for all images. RESULTS: For two out of three observers, the urethra visibility score for 3D HASTE was significantly higher than CT, and clinical bSSFP, but was not significantly different from diagnostic MRI. The mean HD95/MDA/DICE values were 11.35 ± 3.55 mm/5.77 ± 2.69 mm/0.07 ± 0.08 for CT, 7.62 ± 2.75 mm/3.83 ± 1.47 mm/0.12 ± 0.10 for CT + diagnostic MRI, 5.49 ± 2.32 mm/2.18 ± 1.19 mm/0.35 ± 0.19 for 3D TSE, and 6.34 ± 2.89 mm/2.65 ± 1.31 mm/0.21 ± 0.12 for clinical bSSFP. The CNR for 3D HASTE was significantly higher than CT, diagnostic MRI, and clinical bSSFP, but was not significantly different from 3D TSE. CONCLUSION: The urethra's visibility scores showed optimized urethral MRgRT 3D HASTE was superior to the other tested methodologies. The prostatic urethra contours demonstrated significant variability from different imaging and workflows. Urethra contouring uncertainty introduced by cross-modality registration and sub-optimal imaging contrast may lead to significant treatment degradation when urethral sparing is implemented to minimize genitourinary toxicity.

A Framework for Sharing Radiation Dose Distribution Maps in the Electronic Medical Record for Improving Multidisciplinary Patient Management.

Radiation oncology practices use a suite of dedicated software and hardware that are not common to other medical subspecialties, making radiation treatment history inaccessible to colleagues. A radiation dose distribution map is generated for each patient internally that allows for visualization of the dose given to each anatomic structure volumetrically; however, this crucial information is not shared systematically to multidisciplinary medical, surgery, and radiology colleagues. A framework was developed in which dose distribution volumes are uploaded onto the medical center's picture archiving and communication system (PACS) to rapidly retrieve and review exactly where, when, and to what dose a lesion or structure was treated. The ability to easily visualize radiation therapy information allows radiology clinics to incorporate radiation dose into image interpretation without direct access to radiation oncology planning software and data. Tumor board discussions are simplified by incorporating radiation therapy information collectively in real time, and daily onboard imaging can also be uploaded while a patient is still undergoing radiation therapy. Placing dose distribution information into PACS facilitates central access into the electronic medical record and provides a succinct visual summary of a patient's radiation history for all medical providers. More broadly, the radiation dose map provides greater visibility and facilitates incorporation of a patient's radiation history to improve oncologic decision making and patient outcomes. Keywords: Brain/Brain Stem, CNS, MRI, Neuro-Oncology, Radiation Effects, Radiation Therapy, Radiation Therapy/Oncology, Radiosurgery, Skull Base, Spine, Technology Assessment Supplemental material is available for this article. © RSNA, 2021 See also commentary by Khandelwal and Scarboro in this issue.

Online Search Behavior for Cancer Immunotherapy Resources and Readability Analysis: An Opportunity to Aid in Medical Decision-making.

Cancer patients are faced with increasing options for cancer care, especially with the introduction of cancer immunotherapy with immune checkpoint inhibitors (ICIs). Though many patients turn to online resources to supplement their decision-making, it is unknown whether online resources in cancer immunotherapy with ICIs are written at an appropriate level of readability according to national medical organizations. We performed a cross-sectional analysis of internet search behavior for cancer immunotherapy by ICIs and clinical trial availability per ClinicalTrials.gov in the United States (US) from 2004 - 2018 with subsequent quantitation of readability by four readability formulas of top 50 online resources. Internet search behavior for "cancer immunotherapy" has steadily increased since 2013 and coincides with the year of the US Food and Drug Administration (FDA) approval for individual ICIs. Furthermore, internet search behavior was significantly correlated with clinical trial availability in the US (R = 0.97, p < 0.0001). None of the top 50 resources available to patients were found to be within the recommended level of sixth-grade readability or less with only one (2%) written at the middle school level, 21 (42%) at the high school level, 23 (46%) at the university level, and five (8%) at a graduate level. Population-level internet search patterns may reflect patient behavior in seeking relevant online health information and may be influenced by new options for cancer therapy, including via clinical trials. However, low readability of available online resources may impede patient comprehension and negatively affect medical decision-making.

A Matter of Comprehensive Informed Consent: Short-Term Mortality Rates With Definitive Treatment Options in Elderly Stage I NSCLC.

BACKGROUND: Although lobectomy is the standard of care in stage I non-small cell lung cancer (NSCLC), medical comorbidities increase surgical risk in elderly patients. No population-based studies compare short-term mortality (STM) for surgery (STM-S), radiation (STM-R), and observation (STM-O) in elderly patients with stage I NSCLC. METHODS: A total of 60,466 biopsy-proven stage I NSCLC cases diagnosed between 2004 and 2012 were retrieved from the Surveillance, Epidemiology, and End Results Program. Patient characteristics were compared using χ test. Age was divided into 5-year subsets (60 to 64 to 90+ y) for analysis. Similar to other series, STM was defined as death within 2 months of diagnosis. Univariate and multivariate analysis for STM was performed using odds ratio, Kaplan-Meier actuarial method, and Cox proportional hazard ratio. RESULTS: In younger patients, STM-S rates are lower compared with STM-R (1.6% vs. 3.4% in patients 60 to 64 y, P<0.001). However, STM-S rates surpass STM-R with increasing age (up to 8.1% vs. 2.3% in patients 90+ y, P<0.001) becoming significant in the 75- to 79-year age group (4.7% vs. 2.2%, P<0.001). There is an inflection point in the 65- to 69-year age group where STM-S and STM-R rates are similar (2.6% vs. 3.0%, P=0.090). STM for observation reflected the poor health of this cohort with high STM rates in all age groups (19.5% for age 60 to 64 y to 25.3% for age 90+ y, P=0.005). Sex, race, Hispanic ethnicity, age group, and treatment were associated with higher STM on the multivariable analysis (all P<0.001). CONCLUSION: STM in elderly stage I NSCLC patients treated with surgery increases with advancing age but remains stable for patients receiving radiation. Given the success of stereotactic body radiation therapy, radiation should be considered for patients with high STM risk associated with surgery.

Empathic Neural Responses Predict Group Allegiance.

Watching another person in pain activates brain areas involved in the sensation of our own pain. Importantly, this neural mirroring is not constant; rather, it is modulated by our beliefs about their intentions, circumstances, and group allegiances. We investigated if the neural empathic response is modulated by minimally-differentiating information (e.g., a simple text label indicating another's religious belief), and if neural activity changes predict ingroups and outgroups across independent paradigms. We found that the empathic response was larger when participants viewed a painful event occurring to a hand labeled with their own religion (ingroup) than to a hand labeled with a different religion (outgroup). Counterintuitively, the magnitude of this bias correlated positively with the magnitude of participants' self-reported empathy. A multivariate classifier, using mean activity in empathy-related brain regions as features, discriminated ingroup from outgroup with 72% accuracy; the classifier's confidence correlated with belief certainty. This classifier generalized successfully to validation experiments in which the ingroup condition was based on an arbitrary group assignment. Empathy networks thus allow for the classification of long-held, newly-modified and arbitrarily-formed ingroups and outgroups. This is the first report of a single machine learning model on neural activation that generalizes to multiple representations of ingroup and outgroup. The current findings may prove useful as an objective diagnostic tool to measure the magnitude of one's group affiliations, and the effectiveness of interventions to reduce ingroup biases.

Combination anti-Aß treatment maximizes cognitive recovery and rebalances mTOR signaling in APP mice.

Drug development for Alzheimer's disease has endeavored to lower amyloid ß (Aß) by either blocking production or promoting clearance. The benefit of combining these approaches has been examined in mouse models and shown to improve pathological measures of disease over single treatment; however, the impact on cellular and cognitive functions affected by Aß has not been tested. We used a controllable APP transgenic mouse model to test whether combining genetic suppression of Aß production with passive anti-Aß immunization improved functional outcomes over either treatment alone. Compared with behavior before treatment, arresting further Aß production (but not passive immunization) was sufficient to stop further decline in spatial learning, working memory, and associative memory, whereas combination treatment reversed each of these impairments. Cognitive improvement coincided with resolution of neuritic dystrophy, restoration of synaptic density surrounding deposits, and reduction of hyperactive mammalian target of rapamycin signaling. Computational modeling corroborated by in vivo microdialysis pointed to the reduction of soluble/exchangeable Aß as the primary driver of cognitive recovery.

Polar-angle representation of saccadic eye movements in human superior colliculus.

The superior colliculus (SC) is a layered midbrain structure involved in directing both head and eye movements and coordinating visual attention. Although a retinotopic organization for the mediation of saccadic eye-movements has been shown in monkey SC, in human SC the topography of saccades has not been confirmed. Here, a novel experimental paradigm was performed by five participants (one female) while high-resolution (1.2-mm) functional magnetic resonance imaging was used to measure activity evoked by saccadic eye movements within human SC. Results provide three critical observations about the topography of the SC: (1) saccades along the superior-inferior visual axis are mapped across the medial-lateral anatomy of the SC; (2) the saccadic eye-movement representation is in register with the retinotopic organization of visual stimulation; and (3) activity evoked by saccades occurs deeper within SC than that evoked by visual stimulation. These approaches lay the foundation for studying the organization of human subcortical - and enhanced cortical mapping - of eye-movement mechanisms.

Accelerated Changes in Cortical Thickness Measurements with Age in Military Service Members with Traumatic Brain Injury.

Finding objective and quantifiable imaging markers of mild traumatic brain injury (TBI) has proven challenging, especially in the military population. Changes in cortical thickness after injury have been reported in animals and in humans, but it is unclear how these alterations manifest in the chronic phase, and it is difficult to characterize accurately with imaging. We used cortical thickness measures derived from Advanced Normalization Tools (ANTs) to predict a continuous demographic variable: age. We trained four different regression models (linear regression, support vector regression, Gaussian process regression, and random forests) to predict age from healthy control brains from publicly available datasets (n = 762). We then used these models to predict brain age in military Service Members with TBI (n = 92) and military Service Members without TBI (n = 34). Our results show that all four models overpredicted age in Service Members with TBI, and the predicted age difference was significantly greater compared with military controls. These data extend previous civilian findings and show that cortical thickness measures may reveal an association of accelerated changes over time with military TBI.

Real time functional MRI training to decrease motion in imaging studies: Lack of significant improvement.

Functional magnetic resonance imaging (fMRI) is widely used to study brain circuitry in healthy controls and in psychiatry. A major problem of fMRI studies is motion, which affects the quality of images, is a major source of noise, and can confound data if, for example, the experimental groups move differently. Despite continual reminders to experimental subjects about keeping still, however, movement in the scanner remains a problem. The authors hypothesized that showing head movement during a scanning session may help subjects learn how to keep their head still. The authors scanned subjects and displayed in real time a plot of head movement that had three regions. The authors found, in a limited sample, that the improvements were marginal and inconsistent. Thus, they concluded that this strategy, even if likely to work for some people, is probably not sufficiently successful to be implemented at this time.

Are corporations people too? The neural correlates of moral judgments about companies and individuals.

To investigate whether the legal concept of "corporate personhood" mirrors an inherent similarity in the neural processing of the actions of corporations and people, we measured brain responses to vignettes about corporations and people while participants underwent functional magnetic resonance imaging. We found that anti-social actions of corporations elicited more intense negative emotions and that pro-social actions of people elicited more intense positive emotions. However, the networks underlying the moral decisions about corporations and people are strikingly similar, including regions of the canonical theory of mind network. In analyzing the activity in these networks, we found differences in the emotional processing of these two types of vignettes: neutral actions of corporations showed neural correlates that more closely resembled negative actions than positive actions. Collectively, these findings indicate that our brains understand and analyze the actions of corporations and people very similarly, with a small emotional bias against corporations.

Characterizing white matter changes in cigarette smokers via diffusion tensor imaging.

BACKGROUND: Tobacco use remains the most preventable cause of death; however, its effects on the brain, and particularly white matter, remain elusive. Previous diffusion tensor imaging (DTI) studies have failed to yield consistent findings, with some reporting elevated measures of fractional anisotropy (FA) and others reporting lowered FA. METHODS: In our study, we sought to elucidate the effects of tobacco on white matter by using enhanced imaging acquisition parameters and multiple analysis methods, including tract-based spatial statistics (TBSS) with crossing fiber measures and probabilistic tractography. RESULTS: Our TBSS results revealed that chronic cigarette smokers have decreased FA in corpus callosum and bilateral anterior internal capsule, as well as specific reduced anisotropy in the two major fiber directions in a crossing fiber model. Further, our tractography results indicated that smokers have decreased FA in tracts projecting to the frontal cortex from (1) nucleus accumbens, (2) habenula, and (3) motor cortex. We also observed that smokers have greater disruptions in those regions when they had recently smoked compared to when they abstained from smoking for 24h. Our results also support previous evidence showing hemispheric asymmetry, with greater damage to the left side compared to the right. CONCLUSIONS: These findings provide more conclusive evidence of white matter disruptions caused by nicotine use. By better understanding the neural disruptions correlating with cigarette smoking we can elucidate the addictive course and explore targeted treatment regimens for nicotine dependence.