Recurrent (or episodic) fever of unknown origin (FUO) as a variant subgroup of classical FUO: A French multicentre retrospective study of 170 patients.

BACKGROUND: Recurrent FUO (fever of unknown origin) is a rare subtype of FUO for which diagnostic procedures are ill-defined and outcome data are lacking. METHODS: We performed a retrospective multicentre study of patients with recurrent FUO between 1995 and 2018. By multivariate analysis, we identified epidemiological, clinical and prognostic variables independently associated with final diagnosis and mortality. RESULTS: Of 170 patients, 74 (44%) had a final diagnosis. Being ≥ 65 years of age (OR = 5.2; p < 0.001), contributory history (OR = 10.4; p < 0.001), and abnormal clinical examination (OR = 4.0; p = 0.015) independently increased the likelihood of reaching a diagnosis, whereas lymph node and/or spleen enlargement decreased it (OR = 0.2; p = 0.004). The overall prognosis was good; 58% of patients recovered (70% of those with a diagnosis). Twelve (7%) patients died; patients without a diagnosis had a fatality rate of 2%. Being ≥ 65 years of age (OR = 41.3; p < 0.001) and presence of skin signs (OR = 9.5; p = 0.005) significantly increased the risk of death. CONCLUSION: This study extends the known yield of recurrent FUO and highlights the importance of repeated complete clinical examinations to discover potential diagnostic clues during follow-up. Moreover, their overall prognosis is excellent.

Genetic diversity of G9, G3, G8 and G1 rotavirus group A strains circulating among children with acute gastroenteritis in Vietnam from 2016 to 2021.

Rotavirus group A (RVA) is the most common cause of severe childhood diarrhea worldwide. The introduction of rotavirus vaccination programs has contributed to a reduction in hospitalizations and mortality caused by RVA. From 2016 to 2021, we conducted surveillance to monitor RVA prevalence and genotype distribution in Nam Dinh and Thua Thien Hue (TT Hue) provinces where a pilot Rotavin-M1 vaccine (Vietnam) implementation took place from 2017 to 2020. Out of 6626 stool samples, RVA was detected in 2164 (32.6%) by ELISA. RT-PCR using type-specific primers were used to determine the G and P genotypes of RVA-positive specimens. Whole genome sequences of a subset of 52 specimens randomly selected from 2016 to 2021 were mapped using next-generation sequencing. From 2016 to 2021, the G9, G3 and G8 strains dominated, with detected frequencies of 39%, 23%, and 19%, respectively; of which, the most common genotypes identified were G9P[8], G3P[8] and G8P[8]. G1 strains re-emerged in Nam Dinh and TT Hue (29.5% and 11.9%, respectively) from 2020 to 2021. G3 prevalence decreased from 74% to 20% in TT Hue and from 21% to 13% in Nam Dinh province between 2017 and 2021. The G3 strains consisted of 52% human typical G3 (hG3) and 47% equine-like G3 (eG3). Full genome analysis showed substantial diversity among the circulating G3 strains with different backgrounds relating to equine and feline viruses. G9 prevalence decreased sharply from 2016 to 2021 in both provinces. G8 strains peaked during 2019-2020 in Nam Dinh and TT Hue provinces (68% and 46%, respectively). Most G8 and G9 strains had no genetic differences over the surveillance period with very high nucleotide similarities of 99.2-99.9% and 99.1-99.7%, respectively. The G1 strains were not derived from the RVA vaccine. Changes in the genotype distribution and substantial diversity among circulating strains were detected throughout the surveillance period and differed between the two provinces. Determining vaccine effectiveness against circulating strains over time will be important to ensure that observed changes are due to natural secular variation and not from vaccine pressure.

Expert-centered Evaluation of Deep Learning Algorithms for Brain Tumor Segmentation.

Purpose To present results from a literature survey on practices in deep learning segmentation algorithm evaluation and perform a study on expert quality perception of brain tumor segmentation. Materials and Methods A total of 180 articles reporting on brain tumor segmentation algorithms were surveyed for the reported quality evaluation. Additionally, ratings of segmentation quality on a four-point scale were collected from medical professionals for 60 brain tumor segmentation cases. Results Of the surveyed articles, Dice score, sensitivity, and Hausdorff distance were the most popular metrics to report segmentation performance. Notably, only 2.8% of the articles included clinical experts' evaluation of segmentation quality. The experimental results revealed a low interrater agreement (Krippendorff α, 0.34) in experts' segmentation quality perception. Furthermore, the correlations between the ratings and commonly used quantitative quality metrics were low (Kendall tau between Dice score and mean rating, 0.23; Kendall tau between Hausdorff distance and mean rating, 0.51), with large variability among the experts. Conclusion The results demonstrate that quality ratings are prone to variability due to the ambiguity of tumor boundaries and individual perceptual differences, and existing metrics do not capture the clinical perception of segmentation quality. Keywords: Brain Tumor Segmentation, Deep Learning Algorithms, Glioblastoma, Cancer, Machine Learning Clinical trial registration nos. NCT00756106 and NCT00662506 Supplemental material is available for this article. © RSNA, 2023.

Value of ultrasound-guided synovial biopsy for the diagnosis of infectious arthritis.

Objectives: To determine the value of ultrasound (US)-guided synovial biopsy for the diagnosis of infectious arthritis that could not be detected by other modalities. Material and methods: This descriptive study was conducted among 37 patients with arthritis (3 with shoulder arthritis, 2 with elbow arthritis, 7 with wrist arthritis, 15 with hip arthritis, 4 with knee arthritis, and 5 with ankle arthritis) who underwent US-guided synovial biopsy at Hanoi Medical University Hospital for the diagnosis of infec-tious arthritis that could not be detected by infection laboratory tests, imaging, and/or joint fluid culture. The results of US-guided synovial biopsy were positive for infectious arthritis when those of pathologi-cal analyses, bacterial cultures, and/or polymerase chain reaction test for tuberculosis were positive. The final diagnosis established when the patients were discharged from the hospital was compared with the US-guided synovial biopsy results to calculate the sensitivity and specificity for the diagnosis of infectious arthritis. Results: The median age of the patients was 60 years (range: 22-79 years), and two thirds were women. Infectious arthritis was determined as the final diagnosis in 18 patients. There was no significant difference in the infection laboratory test results, synovial thickness, or magnetic resonance imaging features apart from soft tissue abscess between the infectious and non-infectious arthritis groups (P > 0.05). The US-guided synovial biopsy results were positive in 17 patients. Compared with the sensitivity and specificity of the final diagnosis, those of the US-guided synovial biopsy results for the diagnosis of infectious arthritis were 94.4% and 100%, respectively. The Numerical Rating Scale score was ≤3 in most patients. There were neither vascular nor neurologic complications among the patients. Conclusion: Imaging features and laboratory test results are non-specific for infectious arthritis. US-guided synovial biopsy is a well-tolerated, safe method that has a high value for the diagnosis of infectious arthritis. This modality should then be recommended for patients with unclassified arthritis.

A multifunctional soft robotic shape display with high-speed actuation, sensing, and control.

Shape displays which actively manipulate surface geometry are an expanding robotics domain with applications to haptics, manufacturing, aerodynamics, and more. However, existing displays often lack high-fidelity shape morphing, high-speed deformation, and embedded state sensing, limiting their potential uses. Here, we demonstrate a multifunctional soft shape display driven by a 10 × 10 array of scalable cellular units which combine high-speed electrohydraulic soft actuation, magnetic-based sensing, and control circuitry. We report high-performance reversible shape morphing up to 50 Hz, sensing of surface deformations with 0.1 mm sensitivity and external forces with 50 mN sensitivity in each cell, which we demonstrate across a multitude of applications including user interaction, image display, sensing of object mass, and dynamic manipulation of solids and liquids. This work showcases the rich multifunctionality and high-performance capabilities that arise from tightly-integrating large numbers of electrohydraulic actuators, soft sensors, and controllers at a previously undemonstrated scale in soft robotics.

Bavituximab Decreases Immunosuppressive Myeloid-Derived Suppressor Cells in Newly Diagnosed Glioblastoma Patients.

PURPOSE: We evaluated the efficacy of bavituximab-a mAb with anti-angiogenic and immunomodulatory properties-in newly diagnosed patients with glioblastoma (GBM) who also received radiotherapy and temozolomide. Perfusion MRI and myeloid-related gene transcription and inflammatory infiltrates in pre-and post-treatment tumor specimens were studied to evaluate on-target effects (NCT03139916). PATIENTS AND METHODS: Thirty-three adults with IDH--wild-type GBM received 6 weeks of concurrent chemoradiotherapy, followed by 6 cycles of temozolomide (C1-C6). Bavituximab was given weekly, starting week 1 of chemoradiotherapy, for at least 18 weeks. The primary endpoint was proportion of patients alive at 12 months (OS-12). The null hypothesis would be rejected if OS-12 was ≥72%. Relative cerebral blood flow (rCBF) and vascular permeability (Ktrans) were calculated from perfusion MRIs. Peripheral blood mononuclear cells and tumor tissue were analyzed pre-treatment and at disease progression using RNA transcriptomics and multispectral immunofluorescence for myeloid-derived suppressor cells (MDSC) and macrophages. RESULTS: The study met its primary endpoint with an OS-12 of 73% (95% confidence interval, 59%-90%). Decreased pre-C1 rCBF (HR, 4.63; P = 0.029) and increased pre-C1 Ktrans were associated with improved overall survival (HR, 0.09; P = 0.005). Pre-treatment overexpression of myeloid-related genes in tumor tissue was associated with longer survival. Post-treatment tumor specimens contained fewer immunosuppressive MDSCs (P = 0.01). CONCLUSIONS: Bavituximab has activity in newly diagnosed GBM and resulted in on-target depletion of intratumoral immunosuppressive MDSCs. Elevated pre-treatment expression of myeloid-related transcripts in GBM may predict response to bavituximab.

Ten-Year Follow-up of Internal Neurofibroma Growth Behavior in Adult Patients With Neurofibromatosis Type 1 Using Whole-Body MRI.

BACKGROUND AND OBJECTIVES: Internal neurofibromas, including plexiform neurofibromas (PNF), can cause significant morbidity in patients with neurofibromatosis type 1 (NF1). PNF growth is most pronounced in children and young adults, with more rapid growth thought to occur in a subset of PNF termed distinct nodular lesions (DNL). Growth behavior of internal neurofibromas and DNL in older adults is not well documented; yet knowledge thereof is important for patient risk stratification and clinical trial design. The primary objective of this study was to evaluate the long-term growth behavior of internal neurofibromas in adults with NF1. Secondary objectives were to correlate tumor growth behavior with patient-specific, tumor-specific, and patient-reported variables. METHODS: In this prospective cohort study, internal neurofibromas were identified on coronal short TI inversion recovery sequences on baseline and follow-up whole-body MRIs (WBMRIs). Tumor growth and shrinkage were defined as a volume change ≥20%. The association between tumor growth and patient-specific (baseline age, sex, and genotype), tumor-specific (morphology, location, DNL presence on baseline WBMRI, and maximum standardized uptake value on baseline PET imaging), and patient-reported variables (endogenous and exogenous hormone exposure, pain intensity, and quality of life) was assessed using the Spearman correlation coefficient and Kruskal-Wallis test. RESULTS: Of 106 patients with a baseline WBMRI obtained as part of a previous research study, 44 had a follow-up WBMRI. Three additional patients with WBMRIs acquired for clinical care were included, generating 47 adults for this study. The median age during baseline WBMRI was 42 years (range 18-70). The median time between WBMRIs was 10.4 years. Among 324 internal neurofibromas, 62.8% (56% of PNF and 62.1% of DNL) shrank spontaneously without treatment and 17.1% (17.9% of PNF and 13.8% of DNL) grew. Growth patterns were heterogeneous within participants. Patient-specific, tumor-specific, and patient-reported variables (including endogenous and exogenous hormone exposure) were not strong predictors of tumor growth. DISCUSSION: Internal neurofibroma growth behavior in older adults differs fundamentally from that in children and young adults, with most tumors, including DNL, demonstrating spontaneous shrinkage. Better growth models are needed to understand factors that influence tumor growth. These results will inform clinical trial design for internal neurofibromas.

Design of a randomized, placebo-controlled, phase 2 study evaluating the safety and efficacy of tanezumab for treatment of schwannomatosis-related pain.

BACKGROUND: Schwannomatosis (SWN) is a rare tumor suppressor syndrome that predisposes affected individuals to develop multiple schwannomas and, less often, meningiomas. The most common symptom is chronic, severe pain. No medications are broadly effective in treating SWN-associated pain. The clinical trial described in this manuscript is a phase 2, randomized, double-blind, placebo-controlled study investigating the safety and efficacy of tanezumab - a humanized monoclonal antibody that inhibits nerve growth factor - for treatment of SWN-related pain. As the first therapeutic trial for SWN-related pain, it also aims to evaluate trial endpoints, understand recruitment patterns, and improve clinical trial design in this rare disease. AIMS: The primary objective of this trial is to assess the analgesic efficacy of subcutaneous tanezumab 10 mg in subjects with SWN who continue pre-existing pain therapy (excluding non-steroidal anti-inflammatory drugs). The secondary objective is to assess safety in this population. Exploratory objectives include assessment of pain features, quality of life, and predictive biomarkers. METHODS: The study is comprised of four periods (pre-treatment, double-blind treatment, single-arm treatment, safety follow-up) across 10 months with a delayed-start trial design to allow all participants to receive tanezumab. Forty-six participants will be enrolled and randomized 1:1 to receive either tanezumab or placebo subcutaneously in the double-blind treatment period; all participants receive tanezumab during the single-arm treatment period. CONCLUSIONS: This study is the first therapeutic trial for SWN patients and targets a biological driver of SWN-related pain. It aims to establish a model for future pain studies in SWN and other rare diseases. CLINICAL TRIAL REGISTRATION: NCT04163419 on ClinicalTrials.gov.

[Interest of Apremilast in idiopathic recurrent aphthous stomatitis: Review of two clinical cases]. / Intérêt de l'Aprémilast dans les stomatites aphteuses récurrentes idiopathiques : étude de deux cas cliniques.

INTRODUCTION: Apremilast is a phosphodiesterase 4 inhibitor used in psoriasis and psoriatic arthritis Recently, this treatment has received marketing authorization for severe and refractory oral aphthosis in Behçet's disease. Idiopathic recurrent aphthous stomatitis (RAS) outside of Behçet's disease is often difficult to treat and can affect patients' quality of life. CASE REPORTS: We report our experience with the use of apremilast in two 49-year-old patients with refractory oral aphthosis not related to Behçet's disease or another etiology. In both cases, a combination of apremilast with low-dose prednisone controlled the idiopathic RAS within a few weeks. CONCLUSION: Apremilast, which already has marketing authorization for Behçet's disease, also appears to be effective in RAS.

DINs: Deep Interactive Networks for Neurofibroma Segmentation in Neurofibromatosis Type 1 on Whole-Body MRI.

Neurofibromatosis type 1 (NF1) is an autosomal dominant tumor predisposition syndrome that involves the central and peripheral nervous systems. Accurate detection and segmentation of neurofibromas are essential for assessing tumor burden and longitudinal tumor size changes. Automatic convolutional neural networks (CNNs) are sensitive and vulnerable as tumors' variable anatomical location and heterogeneous appearance on MRI. In this study, wepropose deep interactive networks (DINs) to address the above limitations. User interactions guide the model to recognize complicated tumors and quickly adapt to heterogeneous tumors. We introduce a simple but effective Exponential Distance Transform (ExpDT) that converts user interactions into guide maps regarded as the spatial and appearance prior. Comparing with popular Euclidean and geodesic distances, ExpDT is more robust to various image sizes, which reserves the distribution of interactive inputs. Furthermore, to enhance the tumor-related features, we design a deep interactive module to propagate the guides into deeper layers. We train and evaluate DINs on three MRI data sets from NF1 patients. The experiment results yield significant improvements of 44% and 14% in DSC comparing with automated and other interactive methods, respectively. We also experimentally demonstrate the efficiency of DINs in reducing user burden when comparing with conventional interactive methods.

Validating Techniques for Measurement of Cutaneous Neurofibromas: Recommendations for Clinical Trials.

OBJECTIVE: To assess the reliability and variability of digital calipers, 3D photography, and high-frequency ultrasound (HFUS) for measurement of cutaneous neurofibromas (cNF) in patients with neurofibromatosis type 1 (NF1). BACKGROUND: cNF affect virtually all patients with NF1 and are a major source of morbidity. Reliable techniques for measuring cNF are needed to develop therapies for these tumors. METHODS: Adults with NF1 were recruited. For each participant, 6 cNF were assessed independently by 3 different examiners at 5 different time points using digital calipers, 3D photography, and HFUS. The intraclass correlation coefficient (ICC) was used to assess intrarater and interrater reliability of linear and volumetric measurements for each technique, with ICC values >0.90 defined as excellent reliability. The coefficient of variation (CV) was used to estimate the minimal detectable difference (MDD) for each technique. RESULTS: Fifty-seven cNF across 10 participants were evaluated. The ICC for image acquisition and measurement was >0.97 within and across examiners for HFUS and 3D photography. ICC for digital calipers was 0.62-0.88. CV varied by measurement tool, linear vs volumetric measurement, and tumor size. CONCLUSIONS: HFUS and 3D photography demonstrate excellent reliability whereas digital calipers have good to excellent reliability in measuring cNF. The MDD for each technique was used to create tables of proposed thresholds for investigators to use as guides for clinical trials focused on cNF size. These criteria should be updated as the performance of these end points is evaluated.

Imaging Evaluation of Plexiform Neurofibromas in Neurofibromatosis Type 1: A Survey-Based Assessment.

OBJECTIVE: To assess imaging utilization practices across clinical specialists in neurofibromatosis type 1 (NF1) for the evaluation of symptomatic and asymptomatic children and adults with or without plexiform neurofibromas (PN). METHODS: An institutional review board-exempt survey was administered to medical practitioners caring for individuals with NF1 at the Response Evaluation in Neurofibromatosis and Schwannomatosis (REiNS) meeting in September 2019. The survey included questions on respondent demographic data (9 questions), type of imaging obtained for asymptomatic (4 questions) and symptomatic (4 questions) people with and without PN, and utilization of diffusion-weighted imaging (2 questions). RESULTS: Thirty practitioners participated in the survey. Most were academic neuro-oncologists at high-volume (>10 patients/week) NF1 centers. Of 30 respondents, 26 had access to whole-body MRI (WB-MRI). The most common approach to an asymptomatic person without PN was no imaging (adults: 57% [17/30]; children: 50% [15/30]), followed by a screening WB-MRI (adults: 20% [6/30]; children: 26.7% [8/30]). The most common approach to a person with symptoms or known PN was regional MRI (adults: 90% [27/30]; children: 93% [28/30]), followed by WB-MRI (adults: 20% [6/30]; children: 36.7% [11/30]). WB-MRI was most often obtained to evaluate a symptomatic child with PN (37% [11/30]). CONCLUSIONS: More than 90% of practitioners indicated they would obtain a regional MRI in a symptomatic patient without known or visible PN. Otherwise, there was little consensus on imaging practices. Given the high prevalence of PN and risk of malignant conversion in this patient population, there is a need to define imaging-based guidelines for optimal clinical care and the design of future clinical trials.

Giant cell arteritis or polymyalgia rheumatica after influenza vaccination: A study of 12 patients and a literature review.

INTRODUCTION: Giant cell arteritis (GCA) and polymyalgia rheumatica (PMR) are inflammatory rheumatic diseases common in people over the age of 50 years. Seasonal influenza vaccination (IV) is strongly recommended in this population, among whom it is considered to be effective and well tolerated. IV-induced GCA or PMR are thought to be exceptional. PATIENTS AND METHODS: We retrieved all post-IV cases from an inception cohort of patients with newly diagnosed GCA. We also included two patients with post-IV PMR and reviewed all published reports of post-IV GCA or PMR, with selection of cases demonstrating disease onset within 1 month following IV. We compared the results of HLA-DRB1 typing, performed in seven patients with post-IV GCA or PMR, with those of 11 GCA patients with familial aggregation and 16 randomly selected GCA patients without a reported trigger. RESULTS: Of 358 GCA recruited since 2002, 10 (2.8%) qualified for post-IV GCA, of whom two also showed familial aggregation. Thirty-two patients (19 with GCA and 13 with PMR) including our patients were reviewed; their mean age was 71.8 ± 7.4 years and the M/F ratio was 0.8. Six patients (19%) had a history of PMR. Patients with post-IV GCA/PMR had the DRB1*13:01 haplotype more frequently compared to those with familial GCA (5/7 vs. 2/11, p = 0.048) or with GCA without a known trigger (3/16, p = 0.026). Post-IV PMR generally appeared self-limited, whereas post-IV GCA often displayed a more protracted course (chronic relapsing disease in one-third of the patients). CONCLUSION: Post-IV onset of GCA/PMR is not an exceptional occurrence and may be part of the spectrum of the autoimmune syndrome induced by adjuvants (ASIA). IV can trigger GCA or PMR, especially in persons at higher spontaneous risk, such as those with a personal or familial history of GCA/PMR. Whether the presence of the DRB1*13:01 allele further increases the risk of post-IV GCA/PMR through a stronger vaccine-induced immune reaction deserves further investigation. Unlike PMR, GCA can be a serious complication of IV.

DeepNeuro: an open-source deep learning toolbox for neuroimaging.

Translating deep learning research from theory into clinical practice has unique challenges, specifically in the field of neuroimaging. In this paper, we present DeepNeuro, a Python-based deep learning framework that puts deep neural networks for neuroimaging into practical usage with a minimum of friction during implementation. We show how this framework can be used to design deep learning pipelines that can load and preprocess data, design and train various neural network architectures, and evaluate and visualize the results of trained networks on evaluation data. We present a way of reproducibly packaging data pre- and postprocessing functions common in the neuroimaging community, which facilitates consistent performance of networks across variable users, institutions, and scanners. We show how deep learning pipelines created with DeepNeuro can be concisely packaged into shareable Docker and Singularity containers with user-friendly command-line interfaces.

Out-of-office blood pressure measurement for the diagnosis of hypertension in pregnancy: Survey of Canadian Obstetric Medicine and Maternal Fetal Medicine specialists.

BACKGROUND: Multiple hypertension guidelines recommend out-of-office measurements for the diagnosis of hypertension in non-pregnant adults, whereas pregnancy guidelines recommend in-office blood pressure measurements. The objective of our study was to determine how Canadian Obstetric Medicine and Maternal Fetal Medicine specialists measure blood pressure in pregnancy. METHODS: An email survey was sent to 69 Canadian Obstetric Medicine and Maternal Fetal Medicine specialists in academic centers across Canada to explore the practice patterns of blood pressure measurement in pregnant women. RESULTS: The response rate was 48%. The majority of respondents (63.6%) preferred office blood pressure measurement for diagnosing hypertension, but relied on home blood pressure readings for ongoing monitoring and management of hypertension during pregnancy (59.4%). The preferred method of out-of-office blood pressure measurement was home monitoring; 24-hour ambulatory blood pressure monitoring was not used due to limited availability and cost. CONCLUSIONS: There is wide practice variation in methods of measuring blood pressure among Canadian specialists managing hypertension in pregnancy.

Imaging of Central Nervous System Tumors Based on the 2016 World Health Organization Classification.

The 2016 World Health Organization Classification of Tumors of the Central Nervous System (CNS) incorporated well-established molecular markers known to drive tumorigenesis and tumor behavior into the existing classification of CNS tumors based on histopathologic appearance. This integrated classification system has led to a major restructuring of the diffuse gliomas. In addition, it resulted in the categorization of medulloblastomas into four distinct molecular subgroups. Radiogenomic studies have revealed key imaging differences between certain genetic groups and may aid in the diagnosis, longitudinal assessment of treatment response, and evaluation of tumor recurrence in patients with brain tumors.

The Diagnosis and Management of Neurofibromatosis Type 1.

Neurofibromatosis type 1 (NF1), NF2, and schwannomatosis are related, but distinct, tumor suppressor syndromes characterized by a predilection for tumors in the central and peripheral nervous systems. NF1 is one of the most common autosomal dominant conditions of the nervous system. NF1 has a high degree of variability in clinical presentation, which may include multiple neoplasms as well as cutaneous, vascular, bony, and cognitive features. Some of these manifestations overlap with other genetic conditions. Accurate diagnosis of NF1 is important for individualizing clinical care and genetic counseling. This article summarizes the clinical features, diagnostic work-up, and management of NF1.

Automatic assessment of glioma burden: a deep learning algorithm for fully automated volumetric and bidimensional measurement.

BACKGROUND: Longitudinal measurement of glioma burden with MRI is the basis for treatment response assessment. In this study, we developed a deep learning algorithm that automatically segments abnormal fluid attenuated inversion recovery (FLAIR) hyperintensity and contrast-enhancing tumor, quantitating tumor volumes as well as the product of maximum bidimensional diameters according to the Response Assessment in Neuro-Oncology (RANO) criteria (AutoRANO). METHODS: Two cohorts of patients were used for this study. One consisted of 843 preoperative MRIs from 843 patients with low- or high-grade gliomas from 4 institutions and the second consisted of 713 longitudinal postoperative MRI visits from 54 patients with newly diagnosed glioblastomas (each with 2 pretreatment "baseline" MRIs) from 1 institution. RESULTS: The automatically generated FLAIR hyperintensity volume, contrast-enhancing tumor volume, and AutoRANO were highly repeatable for the double-baseline visits, with an intraclass correlation coefficient (ICC) of 0.986, 0.991, and 0.977, respectively, on the cohort of postoperative GBM patients. Furthermore, there was high agreement between manually and automatically measured tumor volumes, with ICC values of 0.915, 0.924, and 0.965 for preoperative FLAIR hyperintensity, postoperative FLAIR hyperintensity, and postoperative contrast-enhancing tumor volumes, respectively. Lastly, the ICCs for comparing manually and automatically derived longitudinal changes in tumor burden were 0.917, 0.966, and 0.850 for FLAIR hyperintensity volume, contrast-enhancing tumor volume, and RANO measures, respectively. CONCLUSIONS: Our automated algorithm demonstrates potential utility for evaluating tumor burden in complex posttreatment settings, although further validation in multicenter clinical trials will be needed prior to widespread implementation.

Publisher Correction: Probing tumor microenvironment in patients with newly diagnosed glioblastoma during chemoradiation and adjuvant temozolomide with functional MRI.

A correction to this article has been published and is linked from the HTML and PDF versions of this paper. The error has been fixed in the paper.