Utilizing connectome fingerprinting functional MRI models for motor activity prediction in presurgical planning: A feasibility study.

Presurgical planning prior to brain tumor resection is critical for the preservation of neurologic function post-operatively. Neurosurgeons increasingly use advanced brain mapping techniques pre- and intra-operatively to delineate brain regions which are "eloquent" and should be spared during resection. Functional MRI (fMRI) has emerged as a commonly used non-invasive modality for individual patient mapping of critical cortical regions such as motor, language, and visual cortices. To map motor function, patients are scanned using fMRI while they perform various motor tasks to identify brain networks critical for motor performance, but it may be difficult for some patients to perform tasks in the scanner due to pre-existing deficits. Connectome fingerprinting (CF) is a machine-learning approach that learns associations between resting-state functional networks of a brain region and the activations in the region for specific tasks; once a CF model is constructed, individualized predictions of task activation can be generated from resting-state data. Here we utilized CF to train models on high-quality data from 208 subjects in the Human Connectome Project (HCP) and used this to predict task activations in our cohort of healthy control subjects (n = 15) and presurgical patients (n = 16) using resting-state fMRI (rs-fMRI) data. The prediction quality was validated with task fMRI data in the healthy controls and patients. We found that the task predictions for motor areas are on par with actual task activations in most healthy subjects (model accuracy around 90%-100% of task stability) and some patients suggesting the CF models can be reliably substituted where task data is either not possible to collect or hard for subjects to perform. We were also able to make robust predictions in cases in which there were no task-related activations elicited. The findings demonstrate the utility of the CF approach for predicting activations in out-of-sample subjects, across sites and scanners, and in patient populations. This work supports the feasibility of the application of CF models to presurgical planning, while also revealing challenges to be addressed in future developments. PRACTITIONER POINTS: Precision motor network prediction using connectome fingerprinting. Carefully trained models' performance limited by stability of task-fMRI data. Successful cross-scanner predictions and motor network mapping in patients with tumor.

Global cancer surgery in low-resource settings: A strengths, weaknesses, opportunities, and threats analysis.

Global cancer surgery is an essential and complex component of oncologic care. This study aims to describe global cancer surgery literature since the 2015 Lancet Commission on Global Surgery and Cancer Surgery and perform a strengths, weaknesses, opportunities, and threats (SWOT) analysis. A systematic search was performed in PubMed of global cancer surgery articles. Themes were extracted from the included studies based on the following criteria: (1) performed in low- or low-middle-income countries, (2) published during or after 2015, (3) published in peer-reviewed journals, (4) written in the English language, and (5) accessible to the authors. Themes were further grouped into strengths, weaknesses, opportunities, and threats (SWOT analysis). The search strategy identified 154 articles published from 1992 to 2022. Forty-six articles were included in the qualitative synthesis and SWOT analysis. Recurring themes included local epidemiologic studies, local innovations and feasibility studies, prioritizing quality of life outcomes, multidisciplinary team approaches, limited resources, health system gaps, lack of economic analyses, diverse cancer management strategies and priorities, inter-setting collaboration, research expansion, the coronavirus disease 2019 pandemic, and unchecked technological advancements. These strengths, weaknesses, opportunities, and threats were described and related to the themes of research, surgical systems strengthening, economics and financing, and political framing of the 2015 Lancet Commission on Global Cancer Surgery. SWOT analyses of global cancer surgery may be helpful in suggesting future strategies for this expanding field. PLAIN LANGUAGE SUMMARY: Cancer surgery is a resource-intensive yet essential component of cancer care. In the face of projected growth of cancer burden, the present gap in cancer surgery care in low-resource settings with stressed health care and surgical infrastructure risks further exacerbation. We present a strengths, weaknesses, opportunities, and threats analysis of recent global cancer surgery literature pertaining to low-resource settings.

Reconstructing the somatotopic organization of the corticospinal tract remains a challenge for modern tractography methods.

The corticospinal tract (CST) is a critically important white matter fiber tract in the human brain that enables control of voluntary movements of the body. The CST exhibits a somatotopic organization, which means that the motor neurons that control specific body parts are arranged in order within the CST. Diffusion magnetic resonance imaging (MRI) tractography is increasingly used to study the anatomy of the CST. However, despite many advances in tractography algorithms over the past decade, modern, state-of-the-art methods still face challenges. In this study, we compare the performance of six widely used tractography methods for reconstructing the CST and its somatotopic organization. These methods include constrained spherical deconvolution (CSD) based probabilistic (iFOD1) and deterministic (SD-Stream) methods, unscented Kalman filter (UKF) tractography methods including multi-fiber (UKF2T) and single-fiber (UKF1T) models, the generalized q-sampling imaging (GQI) based deterministic tractography method, and the TractSeg method. We investigate CST somatotopy by dividing the CST into four subdivisions per hemisphere that originate in the leg, trunk, hand, and face areas of the primary motor cortex. A quantitative and visual comparison is performed using diffusion MRI data (N = 100 subjects) from the Human Connectome Project. Quantitative evaluations include the reconstruction rate of the eight anatomical subdivisions, the percentage of streamlines in each subdivision, and the coverage of the white matter-gray matter (WM-GM) interface. CST somatotopy is further evaluated by comparing the percentage of streamlines in each subdivision to the cortical volumes for the leg, trunk, hand, and face areas. Overall, UKF2T has the highest reconstruction rate and cortical coverage. It is the only method with a significant positive correlation between the percentage of streamlines in each subdivision and the volume of the corresponding motor cortex. However, our experimental results show that all compared tractography methods are biased toward generating many trunk streamlines (ranging from 35.10% to 71.66% of total streamlines across methods). Furthermore, the coverage of the WM-GM interface in the largest motor area (face) is generally low (under 40%) for all compared tractography methods. Different tractography methods give conflicting results regarding the percentage of streamlines in each subdivision and the volume of the corresponding motor cortex, indicating that there is generally no clear relationship, and that reconstruction of CST somatotopy is still a large challenge. Overall, we conclude that while current tractography methods have made progress toward the well-known challenge of improving the reconstruction of the lateral projections of the CST, the overall problem of performing a comprehensive CST reconstruction, including clinically important projections in the lateral (hand and face areas) and medial portions (leg area), remains an important challenge for diffusion MRI tractography.

White matter association tracts underlying language and theory of mind: An investigation of 809 brains from the Human Connectome Project.

Language and theory of mind (ToM) are the cognitive capacities that allow for the successful interpretation and expression of meaning. While functional MRI investigations are able to consistently localize language and ToM to specific cortical regions, diffusion MRI investigations point to an inconsistent and sometimes overlapping set of white matter tracts associated with these two cognitive domains. To further examine the white matter tracts that may underlie these domains, we use a two-tensor tractography method to investigate the white matter microstructure of 809 participants from the Human Connectome Project. 20 association white matter tracts (10 in each hemisphere) are uniquely identified by leveraging a neuroanatomist-curated automated white matter tract atlas. The fractional anisotropy (FA), mean diffusivity (MD), and number of streamlines (NoS) are measured for each white matter tract. Performance on neuropsychological assessments of semantic memory (NIH Toolbox Picture Vocabulary Test, TPVT) and emotion perception (Penn Emotion Recognition Test, PERT) are used to measure critical subcomponents of the language and ToM networks, respectively. Regression models are constructed to examine how structural measurements of left and right white matter tracts influence performance across these two assessments. We find that semantic memory performance is influenced by the number of streamlines of the left superior longitudinal fasciculus III (SLF-III), and emotion perception performance is influenced by the number of streamlines of the right SLF-III. Additionally, we find that performance on both semantic memory & emotion perception is influenced by the FA of the left arcuate fasciculus (AF). The results point to multiple, overlapping white matter tracts that underlie the cognitive domains of language and ToM. Results are discussed in terms of hemispheric dominance and concordance with prior investigations.

Transcranial MR-Guided Focused Ultrasound and Hyperostosis Calvariae Diffusa: Case Report and Systematic Review of the Literature.

We describe a 74-year-old male with intractable essential tremor (ET) and hyperostosis calvariae diffusa who was unsuccessfully treated with magnetic resonance-guided focused ultrasound (MRgFUS). A computed tomography performed prior to the procedure demonstrated a skull density ratio (SDR) of 0.37 and tricortical hyperostosis calvariae diffusa. No lesion was evident on post-MRgFUS MRI, and no improvement in the patient's hand tremor was noted clinically. We systematically reviewed the literature to understand outcomes for those patients with hyperostosis who have undergone MRgFUS. A comprehensive literature search using the PubMed, Cochrane, and Google Scholar databases identified 3 ET patients with hyperostosis who failed treatment with MRgFUS. Clinical findings, skull characteristics, treatment parameters, and outcomes were summarized, demonstrating different patterns/degrees of bicortical hyperostosis and variable SDRs (i.e., from 0.38 to ≥0.45). Although we have successfully treated patients with bicortical hyperostosis frontalis interna (n = 50), tricortical hyperostosis calvariae diffusa appears to be a contraindication for MRgFUS despite acceptable SDRs.

Tractography methods and findings in brain tumors and traumatic brain injury.

White matter fiber tracking using diffusion magnetic resonance imaging (dMRI) provides a noninvasive approach to map brain connections, but improving anatomical accuracy has been a significant challenge since the birth of tractography methods. Utilizing tractography in brain studies therefore requires understanding of its technical limitations to avoid shortcomings and pitfalls. This review explores tractography limitations and how different white matter pathways pose different challenges to fiber tracking methodologies. We summarize the pros and cons of commonly-used methods, aiming to inform how tractography and its related analysis may lead to questionable results. Extending these experiences, we review the clinical utilization of tractography in patients with brain tumors and traumatic brain injury, starting from tensor-based tractography to more advanced methods. We discuss current limitations and highlight novel approaches in the context of these two conditions to inform future tractography developments.

Comparison of multiple tractography methods for reconstruction of the retinogeniculate visual pathway using diffusion MRI.

The retinogeniculate visual pathway (RGVP) conveys visual information from the retina to the lateral geniculate nucleus. The RGVP has four subdivisions, including two decussating and two nondecussating pathways that cannot be identified on conventional structural magnetic resonance imaging (MRI). Diffusion MRI tractography has the potential to trace these subdivisions and is increasingly used to study the RGVP. However, it is not yet known which fiber tracking strategy is most suitable for RGVP reconstruction. In this study, four tractography methods are compared, including constrained spherical deconvolution (CSD) based probabilistic (iFOD1) and deterministic (SD-Stream) methods, and multi-fiber (UKF-2T) and single-fiber (UKF-1T) unscented Kalman filter (UKF) methods. Experiments use diffusion MRI data from 57 subjects in the Human Connectome Project. The RGVP is identified using regions of interest created by two clinical experts. Quantitative anatomical measurements and expert anatomical judgment are used to assess the advantages and limitations of the four tractography methods. Overall, we conclude that UKF-2T and iFOD1 produce the best RGVP reconstruction results. The iFOD1 method can better quantitatively estimate the percentage of decussating fibers, while the UKF-2T method produces reconstructed RGVPs that are judged to better correspond to the known anatomy and have the highest spatial overlap across subjects. Overall, we find that it is challenging for current tractography methods to both accurately track RGVP fibers that correspond to known anatomy and produce an approximately correct percentage of decussating fibers. We suggest that future algorithm development for RGVP tractography should take consideration of both of these two points.

Creation of a novel trigeminal tractography atlas for automated trigeminal nerve identification.

Diffusion MRI (dMRI) tractography has been successfully used to study the trigeminal nerves (TGNs) in many clinical and research applications. Currently, identification of the TGN in tractography data requires expert nerve selection using manually drawn regions of interest (ROIs), which is prone to inter-observer variability, time-consuming and carries high clinical and labor costs. To overcome these issues, we propose to create a novel anatomically curated TGN tractography atlas that enables automated identification of the TGN from dMRI tractography. In this paper, we first illustrate the creation of a trigeminal tractography atlas. Leveraging a well-established computational pipeline and expert neuroanatomical knowledge, we generate a data-driven TGN fiber clustering atlas using tractography data from 50 subjects from the Human Connectome Project. Then, we demonstrate the application of the proposed atlas for automated TGN identification in new subjects, without relying on expert ROI placement. Quantitative and visual experiments are performed with comparison to expert TGN identification using dMRI data from two different acquisition sites. We show highly comparable results between the automatically and manually identified TGNs in terms of spatial overlap and visualization, while our proposed method has several advantages. First, our method performs automated TGN identification, and thus it provides an efficient tool to reduce expert labor costs and inter-operator bias relative to expert manual selection. Second, our method is robust to potential imaging artifacts and/or noise that can prevent successful manual ROI placement for TGN selection and hence yields a higher successful TGN identification rate.

Neural Interactions Underlying Visuomotor Associations in the Human Brain.

Rapid and flexible learning during behavioral choices is critical to our daily endeavors and constitutes a hallmark of dynamic reasoning. An important paradigm to examine flexible behavior involves learning new arbitrary associations mapping visual inputs to motor outputs. We conjectured that visuomotor rules are instantiated by translating visual signals into actions through dynamic interactions between visual, frontal and motor cortex. We evaluated the neural representation of such visuomotor rules by performing intracranial field potential recordings in epilepsy subjects during a rule-learning delayed match-to-behavior task. Learning new visuomotor mappings led to the emergence of specific responses associating visual signals with motor outputs in 3 anatomical clusters in frontal, anteroventral temporal and posterior parietal cortex. After learning, mapping selective signals during the delay period showed interactions with visual and motor signals. These observations provide initial steps towards elucidating the dynamic circuits underlying flexible behavior and how communication between subregions of frontal, temporal, and parietal cortex leads to rapid learning of task-relevant choices.

Mapping cognitive and emotional networks in neurosurgical patients using resting-state functional magnetic resonance imaging.

Neurosurgery has been at the forefront of a paradigm shift from a localizationist perspective to a network-based approach to brain mapping. Over the last 2 decades, we have seen dramatic improvements in the way we can image the human brain and noninvasively estimate the location of critical functional networks. In certain patients with brain tumors and epilepsy, intraoperative electrical stimulation has revealed direct links between these networks and their function. The focus of these techniques has rightfully been identification and preservation of so-called "eloquent" brain functions (i.e., motor and language), but there is building momentum for more extensive mapping of cognitive and emotional networks. In addition, there is growing interest in mapping these functions in patients with a broad range of neurosurgical diseases. Resting-state functional MRI (rs-fMRI) is a noninvasive imaging modality that is able to measure spontaneous low-frequency blood oxygen level-dependent signal fluctuations at rest to infer neuronal activity. Rs-fMRI may be able to map cognitive and emotional networks for individual patients. In this review, the authors give an overview of the rs-fMRI technique and associated cognitive and emotional resting-state networks, discuss the potential applications of rs-fMRI, and propose future directions for the mapping of cognition and emotion in neurosurgical patients.

Preoperative functional MRI use in neurooncology patients: a clinician survey.

OBJECTIVE: Functional MRI (fMRI) is increasingly being investigated for use in neurosurgical patient care. In the current study, the authors characterize the clinical use of fMRI by surveying neurosurgeons' use of and attitudes toward fMRI as a surgical planning tool in neurooncology patients. METHODS: A survey was developed to inquire about clinicians' use of and experiences with preoperative fMRI in the neurooncology patient population, including example case images. The survey was distributed to all neurosurgical departments with a residency program in the US. RESULTS: After excluding incomplete surveys and responders that do not use fMRI (n = 11), 50 complete responses were included in the final analysis. Responders were predominantly from academic programs (88%), with 20 years or more in practice (40%), with a main area of practice in neurooncology (48%) and treating an adult population (90%). All 50 responders currently use fMRI in neurooncology patients, mostly for low- (94%) and high-grade glioma (82%). The leading decision factors for ordering fMRI were location of mass in dominant hemisphere, location in a functional area, motor symptoms, and aphasia. Across 10 cases, language fMRI yielded the highest interrater reliability agreement (Fleiss' kappa 0.437). The most common reasons for ordering fMRI were to identify language laterality, plan extent of resection, and discuss neurological risks with patients. Clinicians reported that fMRI results were not obtained when ordered a median 10% of the time and were suboptimal a median 27% of the time. Of responders, 70% reported that they had ever resected an fMRI-positive functional site, of whom 77% did so because the site was "cleared" by cortical stimulation. Responders reported disagreement between fMRI and awake surgery 30% of the time. Overall, 98% of responders reported that if results of fMRI and intraoperative mapping disagreed, they would rely on intraoperative mapping. CONCLUSIONS: Although fMRI is increasingly being adopted as a practical preoperative planning tool for brain tumor resection, there remains a substantial degree of discrepancy with regard to its current use and presumed utility. There is a need for further research to evaluate the use of preoperative fMRI in neurooncology patients. As fMRI continues to gain prominence, it will be important for clinicians to collectively share best practices and develop guidelines for the use of fMRI in the preoperative planning phase of brain tumor patients.

Test-retest reproducibility of white matter parcellation using diffusion MRI tractography fiber clustering.

There are two popular approaches for automated white matter parcellation using diffusion MRI tractography, including fiber clustering strategies that group white matter fibers according to their geometric trajectories and cortical-parcellation-based strategies that focus on the structural connectivity among different brain regions of interest. While multiple studies have assessed test-retest reproducibility of automated white matter parcellations using cortical-parcellation-based strategies, there are no existing studies of test-retest reproducibility of fiber clustering parcellation. In this work, we perform what we believe is the first study of fiber clustering white matter parcellation test-retest reproducibility. The assessment is performed on three test-retest diffusion MRI datasets including a total of 255 subjects across genders, a broad age range (5-82 years), health conditions (autism, Parkinson's disease and healthy subjects), and imaging acquisition protocols (three different sites). A comprehensive evaluation is conducted for a fiber clustering method that leverages an anatomically curated fiber clustering white matter atlas, with comparison to a popular cortical-parcellation-based method. The two methods are compared for the two main white matter parcellation applications of dividing the entire white matter into parcels (i.e., whole brain white matter parcellation) and identifying particular anatomical fiber tracts (i.e., anatomical fiber tract parcellation). Test-retest reproducibility is measured using both geometric and diffusion features, including volumetric overlap (wDice) and relative difference of fractional anisotropy. Our experimental results in general indicate that the fiber clustering method produced more reproducible white matter parcellations than the cortical-parcellation-based method.

Salvage re-irradiation for recurrent high-grade glioma and comparison to bevacizumab alone.

While salvage re-irradiation is often used for recurrent high-grade glioma (HGG), there have been few comparisons between various re-radiation dose/fractionation schedules or with bevacizumab alone. We analyzed patients with recurrent HGG who received re-irradiation at Dana-Farber Cancer Institute and Brigham and Women's Hospital from 2010 to 2014 (n = 67), as well as those who received bevacizumab alone (n = 177). Cox proportional hazards modeling was used to examine factors associated with overall survival (OS). Propensity score modeling was used to compare survival after re-irradiation vs. bevacizumab alone. Median time from initial diagnosis to re-irradiation was 31.4 months. The most common re-irradiation dose/fractionations used were 6 Gy × 5 (36%), 3.5 Gy × 10 (21%), 2.67 Gy × 15 (15%), and 18-20 Gy × 1 (15%). No early or late toxicities >grade 2 were observed. Median PFS and OS after re-irradiation were 4.8 and 10.7 months, respectively. Number of progressions prior to re-irradiation (adjusted hazard ratio [AHR] 1.6; 95% CI, 1.1-2.3; p = .007), and recurrence in a new brain location (vs. local-only; AHR 7.4; 95% CI, 2.4-23.1; p < .001) were associated with OS; dose/fractionation was not. Compared with bevacizumab alone, re-irradiated patients had a non-significant increase in OS (HR 0.80; 95% CI, 0.53-1.23; P = .31). Among patients with a local-only recurrence, there was a trend towards longer median OS after re-irradiation compared to bevacizumab alone (12.4 vs. 8.0 months; p = .12). Survival after re-irradiation for recurrent HGG appears independent of dose/fractionation and compares favorably with bevacizumab alone.

Intraoperative mass spectrometry mapping of an onco-metabolite to guide brain tumor surgery.

For many intraoperative decisions surgeons depend on frozen section pathology, a technique developed over 150 y ago. Technical innovations that permit rapid molecular characterization of tissue samples at the time of surgery are needed. Here, using desorption electrospray ionization (DESI) MS, we rapidly detect the tumor metabolite 2-hydroxyglutarate (2-HG) from tissue sections of surgically resected gliomas, under ambient conditions and without complex or time-consuming preparation. With DESI MS, we identify isocitrate dehydrogenase 1-mutant tumors with both high sensitivity and specificity within minutes, immediately providing critical diagnostic, prognostic, and predictive information. Imaging tissue sections with DESI MS shows that the 2-HG signal overlaps with areas of tumor and that 2-HG levels correlate with tumor content, thereby indicating tumor margins. Mapping the 2-HG signal onto 3D MRI reconstructions of tumors allows the integration of molecular and radiologic information for enhanced clinical decision making. We also validate the methodology and its deployment in the operating room: We have installed a mass spectrometer in our Advanced Multimodality Image Guided Operating (AMIGO) suite and demonstrate the molecular analysis of surgical tissue during brain surgery. This work indicates that metabolite-imaging MS could transform many aspects of surgical care.

An Electrocorticography Grid with Conductive Nanoparticles in a Polymer Thick Film on an Organic Substrate Improves CT and MR Imaging.

Purpose To develop an electrocorticography (ECoG) grid by using deposition of conductive nanoparticles in a polymer thick film on an organic substrate (PTFOS) that induces minimal, if any, artifacts on computed tomographic (CT) and magnetic resonance (MR) images and is safe in terms of tissue reactivity and MR heating. Materials and Methods All procedures were approved by the Animal Care and Use Committee and complied with the Public Health Services Guide for the Care and Use of Animals. Electrical functioning of PTFOS for cortical recording and stimulation was tested in two mice. PTFOS disks were implanted in two mice; after 30 days, the tissues surrounding the implants were harvested, and tissue injury was studied by using immunostaining. Five neurosurgeons rated mechanical properties of PTFOS compared with conventional grids by using a three-level Likert scale. Temperature increases during 30 minutes of 3-T MR imaging were measured in a head phantom with no grid, a conventional grid, and a PTFOS grid. Two neuroradiologists rated artifacts on CT and MR images of a cadaveric head specimen with no grid, a conventional grid, and a PTFOS grid by using a four-level Likert scale, and the mean ratings were compared between grids. Results Oscillatory local field potentials were captured with cortical recordings. Cortical stimulations in motor cortex elicited muscle contractions. PTFOS implants caused no adverse tissue reaction. Mechanical properties were rated superior to conventional grids (χ(2) test, P < .05). The temperature increase during MR imaging for the three cases of no grid, PTFOS grid, and conventional grid was 3.84°C, 4.05°C, and 10.13°C, respectively. PTFOS induced no appreciable artifacts on CT and MR images, and PTFOS image quality was rated significantly higher than that with conventional grids (two-tailed t test, P < .05). Conclusion PTFOS grids may be an attractive alternative to conventional ECoG grids with regard to mechanical properties, 3-T MR heating profile, and CT and MR imaging artifacts. (©) RSNA, 2016 Online supplemental material is available for this article.

Ambient mass spectrometry for the intraoperative molecular diagnosis of human brain tumors.

The main goal of brain tumor surgery is to maximize tumor resection while preserving brain function. However, existing imaging and surgical techniques do not offer the molecular information needed to delineate tumor boundaries. We have developed a system to rapidly analyze and classify brain tumors based on lipid information acquired by desorption electrospray ionization mass spectrometry (DESI-MS). In this study, a classifier was built to discriminate gliomas and meningiomas based on 36 glioma and 19 meningioma samples. The classifier was tested and results were validated for intraoperative use by analyzing and diagnosing tissue sections from 32 surgical specimens obtained from five research subjects who underwent brain tumor resection. The samples analyzed included oligodendroglioma, astrocytoma, and meningioma tumors of different histological grades and tumor cell concentrations. The molecular diagnosis derived from mass-spectrometry imaging corresponded to histopathology diagnosis with very few exceptions. Our work demonstrates that DESI-MS technology has the potential to identify the histology type of brain tumors. It provides information on glioma grade and, most importantly, may help define tumor margins by measuring the tumor cell concentration in a specimen. Results for stereotactically registered samples were correlated to preoperative MRI through neuronavigation, and visualized over segmented 3D MRI tumor volume reconstruction. Our findings demonstrate the potential of ambient mass spectrometry to guide brain tumor surgery by providing rapid diagnosis, and tumor margin assessment in near-real time.

Salvage whole brain radiotherapy or stereotactic radiosurgery after initial stereotactic radiosurgery for 1-4 brain metastases.

Patients with limited brain metastases are often candidates for stereotactic radiosurgery (SRS) or whole brain radiotherapy (WBRT). Among patients who receive SRS, the likelihood and timing of salvage WBRT or SRS remains unclear. We examined rates of salvage WBRT or SRS among 180 patients with 1-4 newly diagnosed brain metastases who received index SRS from 2008-2013. Competing risks multivariable analysis was used to examine factors associated with time to WBRT. Patients had non-small cell lung (53 %), melanoma (23 %), breast (10 %), renal (6 %), or other (8 %) cancers. Median age was 62 years. Patients received index SRS to 1 (60 %), 2 (21 %), 3 (13 %), or 4 (7 %) brain metastases. Median survival after SRS was 9.7 months (range, 0.3-67.6 months). No further brain-directed radiotherapy was delivered after index SRS in 55 % of patients. Twenty-seven percent of patients ever received salvage WBRT, and 30 % ever received salvage SRS; 12 % of patients received both salvage WBRT and salvage SRS. Median time to salvage WBRT or salvage SRS were 5.6 and 6.1 months, respectively. Age ≤60 years (adjusted hazard ratio [AHR] = 2.80; 95 % CI 1.05-7.51; P = 0.04) and controlled/absent extracranial disease (AHR = 6.76; 95 % CI 1.60-28.7; P = 0.01) were associated with shorter time to salvage WBRT. Isolated brain progression caused death in only 11 % of decedents. In summary, most patients with 1-4 brain metastases receiving SRS never require salvage WBRT or SRS, and the remainder do not require salvage treatment for a median of 6 months.

Incidence, risk factors, and reasons for hospitalization among glioblastoma patients receiving chemoradiation.

Despite a high symptom burden, little is known about the incidence or predictors of hospitalization among glioblastoma patients, including risks during chemoradiation (CRT). We studied 196 consecutive newly diagnosed glioblastoma patients treated at our institution from 2006-2010. Toxicity data were reviewed during and after the CRT phase, defined as the period between diagnosis and 6 weeks after radiotherapy completion. Logistic regression and proportional hazards modeling identified predictors of hospitalization and overall survival (OS). Median age was 59 years (range, 23-90) and 83 % had Karnofsky performance status (KPS) score ≥ 70. Twenty-six percent of patients underwent gross total resection, 77 % received ≥ 59.4 Gy of radiotherapy, and 89 % received concurrent temozolomide. Median OS was 15.6 months (IQR, 8.5-26.8 months). Forty-three percent of patients were hospitalized during the CRT phase; OS was 10.7 vs. 17.8 months for patients who were vs. were not hospitalized, respectively (P < .001). Nearly half of the hospitalizations were due to generalized weakness (17 % of hospitalizations), seizures (16 %), or venous thromboembolism (13 %). On multivariate analysis, age (odds ratio [OR], 1.03; 95 % CI, 1.002-1.060; P = .034) and KPS (OR, 0.95; 95 % CI, 0.93-0.97; P < .001) were associated with risk of hospitalization. Hospitalization during the CRT phase was associated with decreased OS (adjusted hazard ratio, 1.47; 95 % CI, 1.01-2.13; P = .043), after adjustment for known prognostic factors. Hospitalization during the CRT phase is common among glioblastoma patients in the temozolomide era and is associated with shorter overall survival.