Search

GSEA results comparing gene pathway expression differences between the 125 TCGA/TCIA gliomas differentiated by the T2-FLAIR mismatch sign. ES = Enrichment Score. NES = Normalized Enrichment Score. NOM = Nominal. FDR = False Discovery Rate. FWER = Family-wise error rate.

Kaplan-Meier curves demonstrating progression free survival and overall survival associated with the LGGs from the TCGA/TCIA database. Blue curves represent IDHmut-Codel gliomas, dotted black curves represent IDHmut-Noncodel gliomas that were positive for the T2-FLAIR mismatch sign, solid black curves represent IDHmut-Noncodel gliomas that were negative for the T2-FLAIR mismatch sign, and red curves represent IDHwt gliomas.

Purpose: Lower-grade gliomas (WHO grade II/III) have been classified into clinically relevant molecular subtypes based on IDH and 1p/19q mutation status. The purpose was to investigate whether T2/FLAIR MRI features could distinguish between lower-grade glioma molecular subtypes.Experimental Design: MRI scans from the TCGA/TCIA lower grade glioma database (n = 125) were evaluated by two independent neuroradiologists to assess (i) presence/absence of homogenous signal on T2WI; (ii) presence/absence of “T2–FLAIR mismatch” sign; (iii) sharp or indistinct lesion margins; and (iv) presence/absence of peritumoral edema. Metrics with moderate–substantial agreement underwent consensus review and were correlated with glioma molecular subtypes. Somatic mutation, DNA copy number, DNA methylation, gene expression, and protein array data from the TCGA lower-grade glioma database were analyzed for molecular–radiographic associations. A separate institutional cohort (n = 82) was analyzed to validate the T2–FLAIR mismatch sign.Results: Among TCGA/TCIA cases, interreader agreement was calculated for lesion homogeneity [κ = 0.234 (0.111–0.358)], T2–FLAIR mismatch sign [κ = 0.728 (0.538–0.918)], lesion margins [κ = 0.292 (0.135–0.449)], and peritumoral edema [κ = 0.173 (0.096–0.250)]. All 15 cases that were positive for the T2–FLAIR mismatch sign were IDH-mutant, 1p/19q non-codeleted tumors (P < 0.0001; PPV = 100%, NPV = 54%). Analysis of the validation cohort demonstrated substantial interreader agreement for the T2–FLAIR mismatch sign [κ = 0.747 (0.536–0.958)]; all 10 cases positive for the T2–FLAIR mismatch sign were IDH-mutant, 1p/19q non-codeleted tumors (P < 0.00001; PPV = 100%, NPV = 76%).Conclusions: Among lower-grade gliomas, T2–FLAIR mismatch sign represents a highly specific imaging biomarker for the IDH-mutant, 1p/19q non-codeleted molecular subtype. Clin Cancer Res; 23(20); 6078–85. ©2017 AACR.

Background Modifying physician behavior to more closely align with guideline-based care can be challenging. Few effective strategies resulting in appropriate spine-related health care have been reported. The Lumbar Imaging With Reporting of Epidemiology (LIRE) intervention did not result in reductions in spine care but did in opioid prescriptions written. Objectives To estimate organizational resource needs and costs associated with implementing a pragmatic, decision support-type intervention that inserted age- and modality-matched prevalence information for common lumbar spine imaging findings, using site-based resource use data from the LIRE trial. Research design Time and cost estimation associated with implementing the LIRE intervention in a health organization. Subjects Providers and patients assessed in the LIRE trial. Measures Expected personnel costs required to implement the LIRE intervention. Results Annual salaries were converted to daily average per person costs, ranging from $400 to $2,200 per day (base case) for personnel (range: $300-$2,600). Estimated total average cost for implementing LIRE was $5,009 (range: $2,651-$12,020), including conducting pilot testing with providers. Costs associated with a small amount of time for a radiologist (6-12 hours) and imaging-ordering providers (1-8 hours each) account for approximately 75% of the estimated total cost. Conclusions The process of implementing an intervention for lumbar spine imaging reports containing age- and modality-appropriate epidemiological benchmarks for common imaging findings required radiologists, imaging-ordering providers, information technology specialists, and limited testing and monitoring. The LIRE intervention seems to be a relatively low-cost, evidence-based, complementary tool that can be easily integrated into the reporting of spine imaging.

Background: To describe characteristics of patients, providers, and clinics associated with opioid or non-opioid pain medication prescribing patterns for patients who received lower spine imaging in primary care clinics. Methods: In these secondary analyses of the Lumbar Imaging with Reporting of Epidemiology (LIRE) study, a randomized controlled trial conducted in 4 health systems in the United States, we evaluated characteristics associated with receipt of pain medication prescriptions. The outcomes were receipt of prescriptions for opioid or, separately, non-opioid pain medications within 90 days after imaging. Among patients who received opioid or non-opioid prescriptions, we evaluated receipt of multiple prescriptions in the year following imaging. Mixed models were used to estimate adjusted odds ratios (ORs) and 95% confidence intervals (CIs). Results: Compared with whites, patients identified as Asian (OR, 0.53; 95% CI, 0.51–0.56), Native Hawaiian/Pacific Islander (OR, 0.73; 95% CI, 0.64–0.83), multiracial (OR, 0.84; 95% CI, 0.71–0.98) or Black (OR, 0.92; 95% CI, 0.89–0.96) had significantly reduced odds for receiving prescriptions for opioids within 90 days. Patients identified as Native American/Alaska Native had greater odds for receiving prescriptions for non-opioid pain medications within 90 days (OR, 1.12; 95% CI, 1.01–1.24). Receipt of pain prescriptions 120 days before imaging was strongly predictive of subsequent receipt of pain prescriptions across all categories. Conclusions: After adjusting for factors that could affect prescribing, the strongest differences observed in pain-medication prescribing were across racial categories and for patients with previous pain prescriptions. Further research is needed to understand these differences and to optimize prescribing.

Rationale and objectives Recent changes in radiology fellowships include musculoskeletal radiology adopting a match system, interventional radiology transitioning away from diagnostic radiology to offer direct-entry programs, and a common fellowship application timeline created by the Society for Chairs of Academic Radiology Departments (SCARD). The concept of mini-fellowships has also emerged with the elimination of the oral American Board of Radiology examinations that had been administered in the final year of residency training prior to 2014. This paper seeks to assess the opinions of fellowship program directors, residency program directors, and chief residents regarding these recent changes. Materials and methods This is a cross-sectional study using a web-based survey posed to fellowship program directors, residency program directors, and chief residents in 2020. Questions sought to explore current attitudes toward the following topics: (1) a common fellowship application timeline; (2) a common fellowship match; and (3) the status of mini-fellowships in diagnostic radiology. In addition, the number of fellowship positions for each subspecialty was estimated using subspecialty society directories, Accreditation Council for Graduate Medical Education (ACGME) data, and individual program websites. Results Deidentified responses were collected electronically and aggregated. The three respondent groups preferred a common fellowship application timeline at rates of 67% among fellowship program directors, 80% residency program directors, and 74% residents. A common match system across all subspecialties was preferred at rates of 50% fellowship program directors, 74% residency program directors, and 26% chief residents. There was widespread reported compliance with the SCARD fellowship timeline policy. Subspecialty programs using the match system reported interviewing greater numbers of applicants per position. Fellowship directors and chief residents reported that the most common duration of mini-fellowship experiences was 2 to 3 months. Conclusion There is a division between chief residents and program directors regarding the preference for a common radiology match. Adopting a radiology-wide fellowship match would increase the number of interviews required. The SCARD fellowship timeline policy has been successful, and there is support across stakeholders regarding the common timeline. Mini-fellowships are highly variable in length and structure.

Purpose As the COVID-19 pandemic continues, efforts by radiology departments to protect patients and healthcare workers and mitigate disease spread have reduced imaging volumes. This study aims to quantify the pandemic's impact on physician productivity across radiology practice areas as measured by physician work Relative Value Units (wRVUs). Materials and methods All signed diagnostic and procedural radiology reports were curated from January 1st to July 1st of 2019 and 2020. Physician work RVUs were assigned to each study type based on the Medicare Physician Fee Schedule. Utilizing divisional assignments, radiologist schedules were mapped to each report to generate a sum of wRVUs credited to that division for each week. Differential impact on divisions were calculated relative to a matched timeframe in 2019 and a same length pre-pandemic time period in 2020. Results All practice areas saw a substantial decrease in wRVUs from the 2020 pre- to intra-pandemic time period with a mean decrease of 51.5% (range 15.4%–76.9%). The largest declines were in Breast imaging, Musculoskeletal, and Neuroradiology, which had decreases of 76.9%, 75.3%, and 67.5%, respectively. The modalities with the greatest percentage decrease were mammography, MRI, and non-PET nuclear medicine. Conclusion All radiology practice areas and modalities experienced a substantial decrease in wRVUs. The greatest decline was in Breast imaging, Neuroradiology, and Musculoskeletal radiology. Understanding the differential impact of the pandemic on practice areas will help radiology departments prepare for the potential depth and duration of the pandemic by better understanding staffing needs and the financial effects., Highlights • Imaging deferment strategies have been implemented in radiology due to COVID-19. • Deferment strategies have impacted imaging volumes and radiologist productivity. • All practice areas have experienced a decrease in wRVUs. • Breast imaging, Neuroradiology, and MSK radiology experienced the greatest decline.

Objective To evaluate the effect of inserting epidemiological information into lumbar spine imaging reports on subsequent nonsurgical and surgical procedures involving the thoracolumbosacral spine and sacroiliac joints. Design Analysis of secondary outcomes from the Lumbar Imaging with Reporting of Epidemiology (LIRE) pragmatic stepped-wedge randomized trial. Setting Primary care clinics within four integrated health care systems in the United States. Subjects 238,886 patients ≥18 years of age who received lumbar diagnostic imaging between 2013 and 2016. Methods Clinics were randomized to receive text containing age- and modality-specific epidemiological benchmarks indicating the prevalence of common spine imaging findings in people without low back pain, inserted into lumbar spine imaging reports (the “LIRE intervention”). The study outcomes were receiving 1) any nonsurgical lumbosacral or sacroiliac spine procedure (lumbosacral epidural steroid injection, facet joint injection, or facet joint radiofrequency ablation; or sacroiliac joint injection) or 2) any surgical procedure involving the lumbar, sacral, or thoracic spine (decompression surgery or spinal fusion or other spine surgery). Results The LIRE intervention was not significantly associated with subsequent utilization of nonsurgical lumbosacral or sacroiliac spine procedures (odds ratio [OR] = 1.01, 95% confidence interval [CI] 0.93–1.09; P = 0.79) or any surgical procedure (OR = 0.99, 95 CI 0.91–1.07; P = 0.74) involving the lumbar, sacral, or thoracic spine. The intervention was also not significantly associated with any individual spine procedure. Conclusions Inserting epidemiological text into spine imaging reports had no effect on nonsurgical or surgical procedure utilization among patients receiving lumbar diagnostic imaging.

Rationale and Objectives The COVID-19 pandemic has greatly impacted radiology departments across the country. The pandemic has also disrupted resident education, both due to departmental social distancing efforts and reduced imaging volumes. The purpose of this study was to assess the differential impact the pandemic had on radiology resident imaging volumes by training year and imaging modality. Materials and Methods All signed radiology resident reports were curated during defined prepandemic and intrapandemic time periods. Imaging case volumes were analyzed on a mean per resident basis to quantify absolute and percent change by training level. Change in total volume by imaging modality was also assessed. The number of resident workdays assigned outside the normal reading room was also calculated. Results Overall percent decline in resident imaging interpretation volume from the prepandemic to intrapandemic time period was 62.8%. R1s and R2s had the greatest decline at 87.3% and 64.3%, respectively. Mammography, MRI and nuclear medicine had the greatest decline in resident interpretation volume at 92.0%, 73.2%, and 73.0%, respectively. During the intrapandemic time period, a total of 478 resident days (mean of 14.5 days per resident) were reassigned outside of the radiology reading room. Conclusion The COVID-19 pandemic caused a marked decrease in radiology resident imaging interpretation volume and has had a tremendous impact on resident education. The decrease in case interpretation, as well as in-person teaching has profound implications for resident education. Knowledge of this differential decrease by training level will help residency programs plan for the future.

PURPOSE Glioblastoma is extremely infiltrative with malignant cells extending beyond the enhancing rim where recurrence inevitably occurs, despite aggressive multimodal therapy. We hypothesize that important characteristics of peritumoral tissue heterogeneity captured and analyzed by multi-parametric MRI and artificial intelligence (AI) methods are generalizable in the updated multi-institutional ReSPOND (Radiomics Signatures for PrecisiON Diagnostics) consortium and predictive of neoplastic infiltration and future recurrence. METHODS We used the most recent update of the ReSPOND consortium to evaluate and further refine generalizability of our methods with different scanners and acquisition settings. 179 de novo glioblastoma patients with available T1, T1Gd, T2, T2-FLAIR, and ADC sequences at pre-resection baseline and after complete resection with subsequent pathology-confirmed recurrence were included. To establish generalizability of the predictive models, training and testing of the refined AI model was performed through Leave-One-Institution-Out-Cross-Validation schema. The multi-institutional cohort consisted of the Hospital of the University of Pennsylvania (UPenn, 124), Case Western Reserve University/University Hospitals (CWRU/UH, 27), New York University (NYU, 13), Ohio State University (OSU, 13), and University Hospital Río Hortega (RH, 2). Features extracted from pre-resection MRI were used to build the model predicting the spatial pattern of subsequent tumor recurrence. These predictions were evaluated against regions of pathology-confirmed post-resection recurrence. RESULTS Our model predicted the locations that later harbored tumor recurrence with overall odds ratio (99% CI)/AUC (99% CI), 12.0(11.8-12.2)/0.80(0.76-0.85), and per institute, CWRU/UH, 11.0(10.7-11.3)/0.80 (0.64-0.97); NYU, 7.0(6.7-7.3)/0.78(0.56-1.00); OSU, 18.3(17.5-19.1)/0.83(0.54-1.00); RH, 40.0(35.3-45.5)/0.93(0.00-1.00); UPenn, 8.00(7.7-8.3)/0.80(0.75-0.84). CONCLUSION This study provides extensive multi-institutional validated evidence that machine learning tools can identify peritumoral neoplastic infiltration and predict location of future recurrence, by decrypting the MRI signal heterogeneity in peritumoral tissue. Our analyses leveraged the unique dataset of the ReSPOND consortium, which aims to develop and validate AI-based biomarkers for individualized prediction and prognostication and establish generalizability in a multi-institutional setting.

PURPOSE T2-FLAIR mismatch (T2FM) is a highly specific imaging biomarker for isocitrate dehydrogenase (IDH) mutation in low-grade gliomas. Previous T2FM studies are inconsistent for glioblastoma (GBM)/grade-4 glioma, partly due to low IDH-mutation prevalence in high-grade gliomas. We leveraged a large multi-institutional GBM/grade-4 glioma cohort to analyze the association of partial T2FM and IDH-mutation (T2-hyperintense, FLAIR-hypointense, nonenhancing, nonedema). METHODS We analyzed preoperative MRI of 1500 pathologically confirmed GBM/grade-4 gliomas with known IDH-mutation status from the ReSPOND consortium, consisting of the following institutions (sample size): Ivy GBM Atlas Project (33), Catalan Institute of Oncology (132), Case Western Reserve University/University Hospitals (132), New York University (55), Ohio State University (25), University of Pennsylvania (641), University Hospital Río Hortega (16), Yonsei University Health System (118), The Cancer Imaging Archive (93), Thomas Jefferson University (48), Tata Memorial Hospital (22), University of Pittsburgh Medical Center (156), and Washington University School of Medicine in St. Louis (57). Sequences were co-registered to a common anatomic atlas. Continuous variables were compared by t-test and categorical variables by Χ 2-test. RESULTS 71 (4.7%) were IDH-mutants, significantly younger (43±1 v. 62±12 years, p=5x10-37), and more likely to exhibit partial T2FM (20% v. 0.4%, p=1x10-43), frontal lobe predominance (68% v. 29%, p=7x10-12), nonenhancing components (T2/FLAIR-intermediate signal, nonedema; 45% v. 9%, p=1x10-22), and cystic components (smooth margins, no/minimal enhancement, homogeneous FLAIR suppression; 17% v. 3%, p=7x10-11) than IDH-wildtypes. 20 cases had partial T2FM (14 IDH-mutant, 6 IDH-wildtype). Sensitivity of partial T2FM for IDH-mutation was 19.7%, specificity 99.6%, positive predictive value 70%, and negative predictive value 96.1%. Subset analysis of 983 IDH-wildtypes with known MGMT methylation status (406 MGMT-hypermethylated) showed frontal lobe predominance was more common in MGMT-hypermethylated than MGMT-unmethylated (39.4% v. 24.3%, p=.02); other imaging characteristics did not significantly differ. CONCLUSIONS Partial T2FM is a highly specific imaging biomarker for IDH-mutation in GBM/grade-4 glioma.

The modern-day radiologist must be adept at image interpretation, and the one who most successfully leverages new technologies may provide the highest value to patients, clinicians, and trainees. Applications of virtual reality (VR) and augmented reality (AR) have the potential to revolutionize how imaging information is applied in clinical practice and how radiologists practice. This review provides an overview of VR and AR, highlights current applications, future developments, and limitations hindering adoption.

Objective COVID-19 vaccine mandates are being implemented in health systems across the United States and the impact on the radiology department workforce and operations due to vaccine hesitancy among healthcare workers is currently unknown. This article discusses the potential impact of the COVID-19 vaccine mandate on a large multi-center radiology department as well as strategies to mitigate those effects. Methods Weekly vaccine compliance data was obtained for employees across the entire health system from August 17, 2021 through September 13, 2021 and radiology department specific data was extracted. Vaccine compliance data was mapped to specific radiology job titles and the five different hospital locations. Results A total of 6% of radiology department employees were not fully vaccine compliant by the initial deadline of September 10, 2021. Magnetic resonance (MR) technologists and radiology technology assistants had the highest initial rates of non-compliance of 37% and 38%, respectively. Vaccine non-compliance rates by the mandate deadline ranged from 0.5-7.0% at the five hospital sites. Only one hospital required a decrease in imaging hours of operation due to the vaccine mandate. Conclusion Despite initial concerns about the impact of vaccine-mandate non-compliance on departmental operations, there was ultimately little effect due to improved vaccine compliance following the mandate. Understanding individual employee and locoregional differences in vaccine compliance can help leaders proactively develop mitigation strategies to manage this new challenge during the COVID-19 pandemic.

PURPOSE Glioblastoma, IDH-wildtype, is the most common primary malignant adult brain tumor with median overall survival (OS) of ~14 months, with little improvement over the last 20 years. We hypothesize that AI-based integration of quantitative tumor characteristics, independent of acquisition protocol and equipment, can reveal accurate generalizable prognostic stratification. We seek an AI-based OS predictor using routine clinically acquired MRI sequences, quantitatively evaluated across institutions of the ReSPOND (Radiomics Signatures for PrecisiON Diagnostics) consortium. METHODS We identified a retrospective cohort of 2,293 diffuse glioma (IDH-wildtype/-NOS/-NEC) patients from 22 geographically distinct institutions across 3 continents, with preoperative structural MRI scans. The entire tumor burden was automatically segmented into 3 sub-compartments, i.e., enhancing, necrotic, peritumoral T2-FLAIR abnormality. We developed our AI predictor by multivariate integration of i)patient age, ii)tumor sub-compartment volume normalized to brain volume, iii)spatial distribution characteristics (tumor location, distance to the ventricles, and laterality), and iv)morphologic descriptors (major axes’ length, axes’ ratio, extent, and number of tumors). The AI predictor returns a continuous value between 0-1, defining short-, intermediate-, and long-survivors based on thresholds on the 25th and 75th percentiles. Leave-One-Site-Out-Cross-Validation was used to assess the generalizability of our stratification. Kaplan-Meier survival curves were computed for OS analysis and evaluated by a Cox proportional hazards model for statistical significance and hazard ratios. RESULTS Survival analysis yielded a hazard ratio of 2.07 (95%CI, 2.06-2.08, p-value= 4.8e-102) for patient stratification into short-, intermediate-, and long-survivors. Pearson correlation between the predicted and actual OS yielded an R= 0.49. CONCLUSION Multivariate integration of visually quantified tumor characteristics, agnostic to acquisition protocol/equipment, yields an accurate OS surrogate index. Validation of our AI model in the largest centralized glioblastoma imaging dataset, from the ReSPOND consortium, supports its generalizability across diverse patient populations and acquisition settings, potentially contributing to equitable improvements of personalized patient care.

The Association of Program Directors in Radiology (APDR) regularly surveys its members to gather information regarding a broad range of topics related to radiology residency. The survey results provide insight into the opinions of residency program leadership across the country.This is an observational cross-sectional study using a web-based survey posed to the APDR membership in the fall of 2017. The final survey consisted of 53 items, 48 multiple choice questions and five write-in comments. An invitation to complete the survey was sent to all 319 active APDR members.Deidentified responses were collected electronically, tallied utilizing Qualtrics software, and aggregated for the purposes of analysis and reporting at the 66th annual meeting of the Association of University Radiologists. The response rate was 36%.Over the past 16 years, more PDs have assistant and APDs to administer growing residency programs, but the time allocation for these APDs has come from the PD's protected time. An overwhelming majority of PDs consider independent call beneficial to residents and most think a call assistant is desirable. The vast majority of PDs support a unified fellowship match and allow resident moonlighting. Most fourth year residents are actively or moderately involved in clinical work and teaching. The majority of PDs have lost or expect to lose DR training positions to the new IR/DR programs. In a competitive match, PDs do not rely on residency interviews in their selection process.

BACKGROUND Predicting survival of patients with spinal metastases would help stratify treatments from aggressive to palliation. OBJECTIVE To evaluate whether sarcopenia predicts survival in patients with lung, breast, prostate, or multiple myeloma spinal metastases. METHODS Psoas muscle measurements in patients with spinal metastasis were taken from computed tomography scans at 2 time points: at first episode of stereotactic body radiation therapy (SBRT) and from the most recent scan available. Overall survival and hazard ratios were calculated with multivariate cox proportional hazards regression analyses. RESULTS In 417 patients with spinal metastases, 40% had lung cancer, 27% breast, 21% prostate, and 11% myeloma. Overall survival was not associated with age, sex, ethnicity, levels treated, or SBRT volume. Multivariate analysis showed patients in the lowest psoas tertile had shorter survival (222 d, 95% CI = 185-323 d) as compared to the largest tertile (579 d, 95% CI = 405-815 d), (HR1.54, P = .005). Median psoas size as a cutoff value was also strongly predictive for survival (HR1.48, P = .002). Survival was independent of tumor histology. The psoas/vertebral body ratio was also successful in predicting overall survival independent of tumor histology and gender (HR1.52, P

Models of human cancer, to be useful, must replicate human disease with high fidelity. Our focus in this study is rat xenograft brain tumors as a model of human embedded cerebral tumors. A distinguishing signature of such tumors in humans, that of contrast-enhancement on imaging, is often not present when the human cells grow in rodents, despite the xenografts having nearly identical DNA signatures to the original tumor specimen. Although contrast enhancement was uniformly evident in all the human tumors from which the xenografts' cells were derived, we show that long-term contrast enhancement in the model tumors may be determined conditionally by the tumor microenvironment at the time of cell implantation. We demonstrate this phenomenon in one of two patient-derived orthotopic xenograft (PDOX) models using cancer stem-like cell (CSC)-enriched neurospheres from human tumor resection specimens, transplanted to groups of immune-compromised rats in the presence or absence of a collagen/fibrin scaffolding matrix, Matrigel. The rats were imaged by dynamic contrast-enhanced magnetic resonance imaging (DCE-MRI) and their brains were examined by histopathology. Targeted proteomics of the PDOX tumor specimens grown from CSC implanted with and without Matrigel showed that while the levels of the majority of proteins and post-translational modifications were comparable between contrast-enhancing and non-enhancing tumors, phosphorylation of Fox038 showed a differential expression. The results suggest key proteins determine contrast enhancement and suggest a path toward the development of better animal models of human glioma. Future work is needed to elucidate fully the molecular determinants of contrast-enhancement.

AI-based methods have shown great promise in a variety of biomedical research fields, including neurooncologic imaging. For example, machine learning methods have offered informative predictions of overall survival (OS) and progression-free survival (PFS), differentiation between pseudoprogression (PsP) and progressive disease (PD), and estimation of mutational status from imaging data. Despite their promise, AI, and especially the emerging deep learning (DL) methods, are challenged by several factors, including imaging heterogeneity across scanners and lack of sufficiently large and diverse training datasets, which limits their reproducibility and general acceptance. These challenges prompted the development of the ReSPOND (Radiomics Signatures for PrecisiON Diagnostics) consortium on glioblastoma, a growing effort to bring together a community of researchers sharing imaging, demographic, clinical and (currently) limited molecular data in order to address the following aims: 1) pool and harmonize data across diverse hospitals and patient populations worldwide; 2) derive robust and generalizable AI models for prediction of (initially) OS, PFS, PsP vs. PD, and recurrence; 3) test these predictive models across multiple sites. In its first phase, ReSPOND aims to pool together approximately 3,000MRI scans (from 10institutions plus TCIA), along with demographics, KPS, and (for a subset) MGMT/IDH1 status. We present initial results testing the generalization of a previously trained model of OS on 505Penn datasets to 2independent cohorts from Case Western Reserve University and University Hospitals (N=44), and Penn (N=67). The results indicate good generalization, with correlation coefficients between OS/predicted-OS between 0.25 to 0.5, depending on variable availability, which is comparable to cross-validated accuracy previously obtained from the training set itself (N=505). Additional preliminary studies evaluating prediction of future recurrence from baseline pre-operative scans in de novo patients (Penn model applied to CWR) indicated potential for guiding targeted dose escalation and supra-total resection (excellent predictions in 6/12 patients, modest in 1/12, and poor in 5/12).

Large vessel occlusion in patients on ECMO is challenging to appreciate clinically secondary to sedation or induced paralysis, thus placing more emphasis on neurovascular imaging. However, emergent CTA and CTP are both inaccurate and unreliable in ECMO patients due to altered circuitry and interference with normal physiologic hemodynamics. In this review, the utility of DSA is discussed in evaluating the altered hemodynamics of VA-ECMO circuits and patency of major vasculature. In addition, the potential use of TCD in ECMO patients is discussed.

Key Points Question What is the impact of including benchmark prevalence data of common findings in reports of spinal imaging ordered by primary care clinicians? Findings In this randomized clinical trial that included 250 401 adults, no overall decrease in subsequent spine-related health care utilization after the intervention was observed. However, there was a significant decrease in opioid prescriptions at 1 year in the intervention group compared with the control group. Meaning The findings of this study suggest that including epidemiological benchmarks on spinal imaging reports has little impact on subsequent spine-related utilization overall but may reduce subsequent opioid prescriptions., This randomized clinical trial evaluates the impact of including benchmark prevalence data in routine spinal imaging reports on subsequent spine-related health care utilization and opioid prescriptions., Importance Lumbar spine imaging frequently reveals findings that may seem alarming but are likely unrelated to pain. Prior work has suggested that inserting data on the prevalence of imaging findings among asymptomatic individuals into spine imaging reports may reduce unnecessary subsequent interventions. Objective To evaluate the impact of including benchmark prevalence data in routine spinal imaging reports on subsequent spine-related health care utilization and opioid prescriptions. Design, Setting, and Participants This stepped-wedge, pragmatic randomized clinical trial included 250 401 adult participants receiving care from 98 primary care clinics at 4 large health systems in the United States. Participants had imaging of their backs between October 2013 and September 2016 without having had spine imaging in the prior year. Data analysis was conducted from November 2018 to October 2019. Interventions Either standard lumbar spine imaging reports (control group) or reports containing age-appropriate prevalence data for common imaging findings in individuals without back pain (intervention group). Main Outcomes and Measures Health care utilization was measured in spine-related relative value units (RVUs) within 365 days of index imaging. The number of subsequent opioid prescriptions written by a primary care clinician was a secondary outcome, and prespecified subgroup analyses examined results by imaging modality. Results We enrolled 250 401 participants (of whom 238 886 [95.4%] met eligibility for this analysis, with 137 373 [57.5%] women and 105 497 [44.2%] aged >60 years) from 3278 primary care clinicians. A total of 117 455 patients (49.2%) were randomized to the control group, and 121 431 patients (50.8%) were randomized to the intervention group. There was no significant difference in cumulative spine-related RVUs comparing intervention and control conditions through 365 days. The adjusted median (interquartile range) RVU for the control group was 3.56 (2.71-5.12) compared with 3.53 (2.68-5.08) for the intervention group (difference, −0.7%; 95% CI, −2.9% to 1.5%; P = .54). Rates of subsequent RVUs did not differ between groups by specific clinical findings in the report but did differ by type of index imaging (eg, computed tomography: difference, −29.3%; 95% CI, −42.1% to −13.5%; magnetic resonance imaging: difference, −3.4%; 95% CI, −8.3% to 1.8%). We observed a small but significant decrease in the likelihood of opioid prescribing from a study clinician within 1 year of the intervention (odds ratio, 0.95; 95% CI, 0.91 to 1.00; P = .04). Conclusions and Relevance In this study, inserting benchmark prevalence information in lumbar spine imaging reports did not decrease subsequent spine-related RVUs but did reduce subsequent opioid prescriptions. The intervention text is simple, inexpensive, and easily implemented. Trial Registration ClinicalTrials.gov Identifier: NCT02015455

Non-neoplastic sinonasal disease is common and imaging often plays an important role in establishing the proper diagnosis, guiding clinical management, and evaluating for complications. Both computed tomography and magnetic resonance imaging are commonly employed in the imaging evaluation and it is important to understand the imaging characteristics of the unique types of pathology affecting the sinonasal cavities. This article reviews a variety of infectious, inflammatory, and other non-neoplastic sinonasal pathologies, highlighting imaging features that aid in their differentiation.

Coronavirus disease 2019 (COVID-19) is associated with a severe inflammatory response. Inflammation affects atherosclerotic plaque vulnerability and promotes a thrombogenic environment. We report a series of 6 patients with COVID-19 with acute ischemic stroke due to intraluminal carotid artery thrombus presenting during an 8-day period. Six patients were included (5 men) with a mean age of 65.8 years (range, 55–78 years). COVID-19 was diagnosed by detection of Severe Acute Respiratory Syndrome coronavirus 2 in 5 patients and was presumed due to typical clinical and imaging findings in 1 patient. All patients had vascular risk factors including diabetes (83%), hyperlipidemia (100%), and smoking (17%). Four patients presented with large infarcts with initial NIHSS scores of 24–30. During their hospitalization, all patients had elevated D-dimer and C-reactive protein levels, 5 patients had elevated lactate dehydrogenase and ferritin levels, 3 had elevated interleukin-6 levels, and 2 had elevated troponin levels. Inflammation related to COVID-19 may result in rupture of vulnerable atherosclerotic plaques, resulting in thrombosis and acute ischemic stroke.

BACKGROUND: Information on the prevalence of common imaging findings among patients without back pain in spine imaging reports might affect pain medication prescribing for patients with back pain. Prior research on inserting this text suggested a small reduction in opioid prescribing. OBJECTIVE: To evaluate the effect of epidemiologic information in spine imaging reports on non-opioid pain medication prescribing for primary care patients with back pain. DESIGN: Post hoc analysis of the Lumbar Imaging with Reporting of Epidemiology cluster-randomized trial. PARTICIPANTS: A total of 170,680 patients aged ≥ 18 years from four healthcare systems who received thoracolumbar, lumbar, or lumbosacral spine imaging from 2013 to 2016 and had not received a prescription for non-opioid pain medication in the preceding 120 days. INTERVENTION: Text of age- and modality-specific epidemiologic benchmarks indicating the prevalence of common findings in people without back pain inserted into thoracolumbar, lumbar, or lumbosacral spine imaging reports at intervention clinics. MAIN MEASURES: Primary outcomes: any non-opioid prescription within 90 days after index imaging, overall, and by sub-class (skeletal muscle relaxants, NSAIDs, gabapentinoids, tricyclic antidepressants, benzodiazepines, duloxetine). Secondary outcomes: count of non-opioid prescriptions within 90 days, overall, and by sub-class. KEY RESULTS: The intervention was not associated with the likelihood of patients receiving at least one prescription for new non-opioid pain-related medications, overall (adjusted OR, 1.02; 95% CI, 0.97–1.08) or by sub-class. The intervention was not associated with the number of prescriptions for any non-opioid medication (adjusted incidence rate ratio [IRR], 1.02; 95% CI, 0.99–1.04). However, the intervention was associated with more new prescriptions for NSAIDs (IRR, 1.12) and tricyclic antidepressants (IRR, 1.11). CONCLUSIONS: Inserting epidemiologic text in spine imaging reports had no effect on whether new non-opioid pain-related medications were prescribed but was associated with the number of new prescriptions for certain non-opioid sub-classes. TRIAL REGISTRATION: ClinicalTrials.gov identifier: NCT02015455 SUPPLEMENTARY INFORMATION: The online version contains supplementary material available at 10.1007/s11606-021-06627-6.

Systemic lupus erythematosus is a chronic autoimmune disease characterized by the production of autoantibodies resulting in tissue injury across multiple organs; up to 50% of patients develop neurologic involvement, collectively referred to as neuropsychiatric systemic lupus erythematosus. The cases in this clinical report will highlight a subtype of neuropsychiatric systemic lupus erythematosus demonstrating imaging findings of striatal inflammation responsive to plasmapheresis similar to those in the subset of N-methyl-D-aspartate receptor autoimmune encephalitis that involves the striatum. Although the cause for this striking imaging appearance is not definitely known, literature will be presented supporting the hypothesis that it is due to peripheral anti-double-stranded DNA antibodies entering the central nervous system to cross-react with N-methyl-D-aspartate receptor antigens.

Intramedullary spinal lesions present a wide differential diagnosis including infectious, inflammatory, traumatic, ischemic, benign, or malignant neoplastic etiologies. Using knowledge of anatomy and physiology within the spinal cord, many similar appearing entities can be parsed into a prioritized differential. The purpose of this article is to review anatomy and pathophysiology of the spinal cord, with subsequent discussion of how this knowledge can be used to differentiate several similar appearing intramedullary pathologic processes. Discussion includes the pathophysiology, imaging findings, and clinical pearls of several intramural lesions including infarct, demyelinating lesions, traumatic injury, neoplasm, vascular malformation, and metabolic processes such as subacute combined degeneration.

Rationale and Objectives The Electronic Resident Application Service (ERAS) publishes monthly statistics before the match and the National Resident Matching Program publishes the match outcomes. We sought to determine whether early ERAS data influences applicant behavior and correlates with match outcomes. Materials and Methods We searched the 2007–2017 ERAS archives for the applicant pool size (PS), the average number of applications per program (AP), and the average number of applications per applicant (AA) in November, before radiology match, and the 2007–2017 National Resident Matching Program archives for the average number of ranked applicants needed to fill each position (ANRA) and the number of unfilled positions (UP) in radiology match. Correlation coefficients were calculated for each pair. Results PS correlated very strongly with AP (r = 0.80, p = 0.001708), UP (r = −0.92, p = 0.000063) and ANRA (r = −0.90, p = 0.000164). UP correlated strongly with ANRA (r = 0.76, p = 0.006349) and AP (r = −0.77, p = 0.005339). A trend to moderate correlation between AP and ANRA (r = 0.58, p = 0.062686) and AA (r = 0.53, p = 0.074395) did not reach statistical significance. There was no correlation between AA and PS in the same (r = −0.05, p = 0.878585) or the following year (r = 0.35, p = 0.297166), and AA and UP in the same (r = 0.13, p = 0.701983) or the following year (r = 0.32, p = 0.336136). Conclusion The real-time data reported by ERAS in November, before match, is a predictor of radiology match outcomes and can be used by all participants to limit their application and recruitment costs. Medical students applying to radiology do not consider either the real-time or historic data when submitting ERAS applications.

Background Context The current standard of care for prediction of survival of cancer staging is based on TNM staging. However, for patients with spinal metastasis, who all have identical stage IV disease, identifying accurate prognostic markers of survival would allow better treatment stratification between more aggressive treatment strategies or palliation. Analytical morphometrics enables physicians to quantify patient frailty by measuring lean muscle mass. Morphometrics also predicts survival in patients with lung cancer metastases to the spine. Purpose Our study evaluates whether morphometrics is predictive of survival in patients with breast cancer spinal metastasis. Design This is an observational retrospective cohort study. Patient Sample This study includes female patients with breast cancer spinal metastases and patients who have undergone stereotactic body radiation therapy. Outcome Measures Overall survival was the primary outcome measure. Methods Morphometric measurements of the psoas muscle were taken using computed tomography scans of the lumbar spine. We then stratified patients into tertiles based on the psoas muscle area. Results We identified 118 patients, with a median survival of 104 days (95% confidence interval [CI]=73–157 days). Overall survival was not associated with age, chemotherapy, or number of levels radiated. Patients in the lowest tertile of psoas size had significantly shorter survival compared with the highest tertile (68 days versus 148 days, hazard ratio 1.76 [95% CI=1.08–2.89], p=.024). The shorter survival was also true for the lowest tertile versus the middle tertile (68 days versus 167 days, hazard ratio 1.95 [95% CI=1.19–3.19], p=.007). Kaplan-Meier survival curves were used to visually illustrate the differences in survival between different tertiles. Conclusions Morphometric analysis of the psoas muscle size in patients with breast cancer metastases to the spine was effective in identifying patients at risk of shorter survival. Further research is needed to validate these results, as well as to see if these methodologies can be applied to other cancer histologies.

BACKGROUND AND PURPOSE: Idiopathic intracranial hypertension is a complex neurologic disorder resulting from increased intracranial pressure. Our aim was to determine whether a correlation exists between the CSF pressure-volume relationship, specifically the craniospinal elastance and pressure-volume index, in patients with idiopathic intracranial hypertension and whether opening pressure affects this relationship. MATERIALS AND METHODS: Lumbar punctures performed for suspected idiopathic intracranial hypertension from 2006 to 2017 were identified. Opening and closing pressures, CSF volume removed, and clinical diagnosis of idiopathic intracranial hypertension were obtained from the medical records. The craniospinal elastance (pressure change per milliliter of CSF removed) and pressure-volume index were calculated, and the Pearson correlation coefficients between both the craniospinal elastance and pressure-volume index and opening pressure were determined. Linear regression models of craniospinal elastance and the pressure-volume index and interaction terms with opening pressure were assessed for covariate influence on this association. RESULTS: One hundred sixteen patients were included in the final analysis. The mean craniospinal elastance according to opening pressure group was 0.52 ± 0.18 for

Funding for research has become increasingly difficult to obtain in an environment of decreasing clinical revenue, increasing research costs, and growing competition for federal and nonfederal funding sources. This paper identifies critical requirements to build and sustain a successful radiology research program (eg, key personnel and leadership, research training and mentorship, infrastructure, institutional and departmental funding or support), reviews the current state of available funding for radiology (including federal, nonfederal, philanthropy, crowdfunding, and industry), and describes promising opportunities for future funding (eg, health services, comparative effectiveness, and patient-centered outcomes research). The funding climate, especially at the federal level, changes periodically, so it is important to have radiology-specific organizations such as the American College of Radiology and the Academy of Radiology Research serving as our key advocates. Key to obtaining any funding, no matter what the source, is a well-formulated grant proposal, so a review of opportunities specifically available to radiologists to develop and hone their grant-writing skills is provided. Effective and sustained funding for radiology research has the potential to cultivate young researchers, bolster quality research, and enhance health care. Those interested in pursuing research need to be aware of the ever-changing funding landscape, research priority areas, and the resources available to them to succeed. To succeed, radiology researchers need to think about diversification and flexibility in their interests, developing multidisciplinary and multi-institutional projects, and engaging a broader base of stakeholders that includes patients.

Purpose: Lower-grade gliomas (WHO grade II/III) have been classified into clinically relevant molecular subtypes based on IDH and 1p/19q mutation status. The purpose was to investigate whether T2/FLAIR MRI features could distinguish between lower-grade glioma molecular subtypes. Experimental Design: MRI scans from the TCGA/TCIA lower grade glioma database (n = 125) were evaluated by two independent neuroradiologists to assess (i) presence/absence of homogenous signal on T2WI; (ii) presence/absence of “T2–FLAIR mismatch” sign; (iii) sharp or indistinct lesion margins; and (iv) presence/absence of peritumoral edema. Metrics with moderate–substantial agreement underwent consensus review and were correlated with glioma molecular subtypes. Somatic mutation, DNA copy number, DNA methylation, gene expression, and protein array data from the TCGA lower-grade glioma database were analyzed for molecular–radiographic associations. A separate institutional cohort (n = 82) was analyzed to validate the T2–FLAIR mismatch sign. Results: Among TCGA/TCIA cases, interreader agreement was calculated for lesion homogeneity [κ = 0.234 (0.111–0.358)], T2–FLAIR mismatch sign [κ = 0.728 (0.538–0.918)], lesion margins [κ = 0.292 (0.135–0.449)], and peritumoral edema [κ = 0.173 (0.096–0.250)]. All 15 cases that were positive for the T2–FLAIR mismatch sign were IDH-mutant, 1p/19q non-codeleted tumors (P < 0.0001; PPV = 100%, NPV = 54%). Analysis of the validation cohort demonstrated substantial interreader agreement for the T2–FLAIR mismatch sign [κ = 0.747 (0.536–0.958)]; all 10 cases positive for the T2–FLAIR mismatch sign were IDH-mutant, 1p/19q non-codeleted tumors (P < 0.00001; PPV = 100%, NPV = 76%). Conclusions: Among lower-grade gliomas, T2–FLAIR mismatch sign represents a highly specific imaging biomarker for the IDH-mutant, 1p/19q non-codeleted molecular subtype. Clin Cancer Res; 23(20); 6078–85. ©2017 AACR.

INTRODUCTION Pre-operative differentiation of IDH mutant gliomas from similar appearing pathologies on imaging prior to definitive surgical diagnosis may aid treatment navigation, maximize the surgical approach, and provide diagnostic support for inoperable tumors. Quantitative image feature analysis offers a potential non-invasive method to identify diagnostic, prognostic, and predictive imaging biomarkers. We investigated the use of radiomic MR imaging features to classify tumors based on IDH mutation status. METHOD Pre-operative T1-weighted (T1W), T2-weighted (T2W), T1-contrast enhanced (T1CE), and fluid attenuated inversion recovery (FLAIR) MR brain images, along with patient IDH mutation status (mutant/wildtype) were obtained for 128 glioma patients from The Cancer Genome Atlas (TCGA). Enhancing tumor was delineated by GLISTRboost. GlistrBoost is a hybrid-discriminative model that segments tumors based on an expectation-maximization framework with a classification scheme and uses a probabilistic Bayesian strategy for segmentation refinement. MR studies for 78 glioma patients from six institutions were used for training and 50 glioma patients from a different institution were used for validation. Pre-processing included registration, resampling, and normalization. Cancer Imaging Phenomics Toolkit (CaPTK) extracted 938 radiomic image features per sequence for the enhancing tumor contour. Relevance of each individual feature was determined by the least absolute shrinkage and selection operator (LASSO). The ability of relevant radiomic image features to identify mutation status of IDH was assessed by logistic regression. RESULTS LASSO identified one highly informative radiomic imaging feature, the minimum of the mean absolute histogram deviation on T1 MR images, which was able to predict IDH mutation status with an accuracy of 0.74, precision of 1.0, and recall of 0.32. CONCLUSION Non-invasive prediction of IDH mutation status from pre-surgical MR images offers potential diagnostic, therapeutic, and prognostic benefits for glioma patients. Quantitative image feature analysis is a feasible method for identifying potential radiomic imaging features.

In murine models, patient derived orthotopic xenografts (PDOXs) generated from neurosphere cultures of human glioblastomas (GBMs) are unmatched in representing the molecular heterogeneity of the disease. However, intra-axial tumors with blood-brain barrier (BBB) breakdown visible on magnetic resonance imaging (MRI) are rare in these models and, thus, phenotypic recapitulation of human tumors is typically absent. We hypothesized that this absence lay in the interaction between tumor and stroma and that manipulation of the tumor stromal composition might produce a consistent BBB breakdown. Thirty-two athymic nude rats were implanted intracerebrally with one of two neurosphere cell lines (HF2303 or HF3016) derived from the tumors of two GBM patients demonstrating post-gadolinium enhancement on MRI. Neurospheres (3x105 cells in 10μl) were co-injected with a preparation containing either 5μl Matrigel with high (M+) or low (M-) growth factors, or PBS (M0). When the lesion reached 4 to 5 mm in diameter on imaging, MRI with contrast was used to study BBB breakdown. Two animals with only extra-axial tumors were excluded from analysis, and the intra-axial tumors were graded for radiological evidence of BBB breakdown on a scale of 0 to 4, with 0 being no evidence, and 4 being florid enhancement. A two-way ordinal logistic regression model was fit with treatment factors (three levels: M0, M+ and M-) and cell line (two levels: HF2303 and HF3016). A Wilcoxon Rank Sum test analysis within each cell line demonstrated a significant BBB breakdown effect with Matrigel in HF3016 (N=16, p=0.004), but not for HF2303 (N=16, p=0.328). By producing phenotypic conditions closer to the human glioma pathology, a reliable BBB breakdown in PDOX models represents a significant advance in assessing experimental therapies. However, as demonstrated herein, the effect of stromal enhancement is cell-line dependent, and the biological correlates that accompany BBB breakdown still need to be described.

Radiologists are facing ever increasing volumes while trying to provide value-based care. There are several drivers of increasing volumes: increasing population size, aging population, increased utilization, gaps in evidence-based care, changes in the provider workforce, defensive medicine, and increasing case complexity. Higher volumes result in increased cognitive and systemic errors and contribute to radiologist fatigue and burnout. We discuss several strategies for mitigating high volumes including abbreviated MRI protocols, 24/7 radiologist coverage, reading room assistants, and other strategies to tackle radiologist burnout.

The anterior cerebral artery (ACA) contains anatomical variants that are closely related to its embryology and development. In this study, the authors reviewed the most commonly encountered variants of the ACA and anterior communicating artery. They also reviewed the embryological origins of these variants as well as a variety of associated pathologies. Several variants are described and highlighted with illustrations including: (1) the aberrant origin of the ACA from the internal carotid artery and its developmental association with the ophthalmic artery; (2) the persistent olfactory artery; (3) the azygous ACA; (4) the triplicated ACA; and (5) multiple anterior communicating arteries. The formation of aneurysms is associated with such variants, thus their knowledge and the embryology behind their development are crucial to prevent injury to the patient.

Background and objectives Laser interstitial thermal therapy (LITT) is a minimally invasive therapeutic option for the treatment of brain tumors. Previous studies have quantitatively followed the ablated volumes of high-grade gliomas. Reported treatment volumes range from 28% to 100%, with no reported interobserver analysis. Because these volumes are subjectively measured, it is necessary to establish concordance between clinicians. Study design/materials and methods Utilizing Brainlab tumor analysis software (Brainlab, Munich, Germany), five physician users traced out tumor volumes slice-by-slice on 10 treated tumors in eight patients. The participants were briefed with specific instructions and a demonstration on how to trace the enhancing borders of the tumor slice-by-slice. Volumes automatically calculated by the Brainlab software included preoperative, intraoperative ablation and postoperative enhancing volumes. Data regarding size, cystic appearance, pathology, previous surgery, and demographics were included. Results The intraclass correlation coefficient (ICC) for preoperative, intraoperative, and postoperative volumes was 0.92 (95% confidence interval, [CI] 0.81-0.97), 0.90 (0.77-0.96), and 0.89 (0.74-0.96), respectively. The overall ICC was 0.72 (0.50-0.87). ICC comparisons were also made for each pair of readers (neuroradiologist, neuro-oncologist, senior neurosurgery resident, neurosurgery junior resident) which resulted in pretreatment ICC scores of 0.97, 0.91, 0.66, 0.94; intratreatment scores of 0.97, 0.78, 0.90, 0.96; and posttreatment scores of 0.96, 0.81, 0.89, and 0.87. A Bland-Altman plot was also used to assess the differences in volumes. Conclusions The ICC gives a composite of the consistency of measurements made by multiple observers measuring the same quantity. The overall ICC of 0.72 means there is good correlation between observers in our study between measured volumes. Lasers Surg. Med. © 2019 Wiley Periodicals, Inc.

Introduction: Computed tomographic angiography (CTA) is an important initial assessment for detecting large vessel occlusion (LVO) in acute ischemic stroke (AIS) and for selecting patients for mechanical thrombectomy (MT). This study is designed to evaluate the impact of an emergency CTA protocol on outcome of AIS patients with LVO. Methods: On July 1, 2017 we implemented the policy of performing CTA at the same time as non-contrast CT (NCCT) in all AIS patients presenting within 24 hours of symptom onset regardless of baseline NIHSS. Previously emergency CTA was reserved for patients presenting within 6 hours with an NIHSS ≥6. We compared treatment processes and outcomes between AIS patients admitted 1-year before (N=396) and 1-year after (N=494) protocol implementation. Results: After protocol implementation, more patients underwent CTA (90% vs 60%, P < 0.001) and had CTA performed at the time of the initial NCCT (77% vs 34%, P Conclusion: Emergency CTA for all stroke patients presenting within 24 hours regardless of baseline NIHSS improves LVO detection, increases the MT treatment population, speeds intervention, and improves outcome after LVO. The benefit primarily affects patients who present within 6 hours of symptom onset.

INTRODUCTION Magnetic resonance imaging (MRI) is a fundamental component of longitudinal neuro-oncology evaluation and decision-making. The Response Assessment in Neuro-Oncology criteria for low-grade gliomas (RANOLGG) was designed as an outcome measure for clinical trials. Thus, this project intends to study the reliability of RANOLGG in the clinic setting. METHODS 21 pairs of brain MRIs, that averaged three years apart, were selected from 21 patients with tissue diagnosis of WHO grade 2 gliomas. Two neuro-oncologists and two neuro-radiologists reviewed and independently scored the MRI pairs according to RANOLGG categories of progressive disease, stable disease, minor response, partial response, and complete response. Kappa-Fleiss (KF) was used to evaluate agreement among reviewers. RESULTS Reviewers awarded identical scores in only 33% of MRI pairs and there was a complete disagreement in one MRI pair. Overall reliability of the criteria in the clinical setting is moderate (KF = 0.44). Agreement between neuroradiologists (KF = 0.51) and between neuro-oncologists (KF = 0.48) were similar. Interpretation of post-contrast T1-weighted images had a better agreement (KF = 0.31) than T2/FLAIR-weighted images which had a poor agreement (KF = -0.02). Classification of progression versus non-progression had only a moderate agreement (KF= 0.49). History of radiation therapy or chemotherapy did not influence the criteria reliability (fisher exact text, p = 0.58, p =0.27, respectively). CONCLUSION RANOLGG reliability in the clinical setting is moderate, therefore it should be used cautiously for clinical decision-making. Other tools that can support the neuro-oncologist in the follow-up of patients with low-grade glioma are additional MRI sequences other than T2/FLAIR and contrast – weighted images, computer-aided diagnosis such as volumetrics, spectroscopy, positron emission tomography, and multidisciplinary tumor boards. Likewise, when image criteria for low-grade gliomas are designed, T2/FLAIR should be used guardedly, due to low interpretation agreement.