Detecting Large Vessel Occlusion at Multiphase CT Angiography by Using a Deep Convolutional Neural Network.

Background Large vessel occlusion (LVO) stroke is one of the most time-sensitive diagnoses in medicine and requires emergent endovascular therapy to reduce morbidity and mortality. Leveraging recent advances in deep learning may facilitate rapid detection and reduce time to treatment. Purpose To develop a convolutional neural network to detect LVOs at multiphase CT angiography. Materials and Methods This multicenter retrospective study evaluated 540 adults with CT angiography examinations for suspected acute ischemic stroke from February 2017 to June 2018. Examinations positive for LVO (n = 270) were confirmed by catheter angiography and LVO-negative examinations (n = 270) were confirmed through review of clinical and radiology reports. Preprocessing of the CT angiography examinations included vasculature segmentation and the creation of maximum intensity projection images to emphasize the contrast agent-enhanced vasculature. Seven experiments were performed by using combinations of the three phases (arterial, phase 1; peak venous, phase 2; and late venous, phase 3) of the CT angiography. Model performance was evaluated on the held-out test set. Metrics included area under the receiver operating characteristic curve (AUC), sensitivity, and specificity. Results The test set included 62 patients (mean age, 69.5 years; 48% women). Single-phase CT angiography achieved an AUC of 0.74 (95% confidence interval [CI]: 0.63, 0.85) with sensitivity of 77% (24 of 31; 95% CI: 59%, 89%) and specificity of 71% (22 of 31; 95% CI: 53%, 84%). Phases 1, 2, and 3 together achieved an AUC of 0.89 (95% CI: 0.81, 0.96), sensitivity of 100% (31 of 31; 95% CI: 99%, 100%), and specificity of 77% (24 of 31; 95% CI: 59%, 89%), a statistically significant improvement relative to single-phase CT angiography (P = .01). Likewise, phases 1 and 3 and phases 2 and 3 also demonstrated improved fit relative to single phase (P = .03). Conclusion This deep learning model was able to detect the presence of large vessel occlusion and its diagnostic performance was enhanced by using delayed phases at multiphase CT angiography examinations. © RSNA, 2020 Online supplemental material is available for this article. See also the editorial by Ospel and Goyal in this issue.

Detection of emergent large vessel occlusion stroke with CT angiography is high across all levels of radiology training and grayscale viewing methods.

OBJECTIVES: CT angiography (CTA) is essential in acute stroke to detect emergent large vessel occlusions (ELVO) and must be interpreted by radiologists with and without subspecialized training. Additionally, grayscale inversion has been suggested to improve diagnostic accuracy in other radiology applications. This study examines diagnostic performance in ELVO detection between neuroradiologists, non-neuroradiologists, and radiology residents using standard and grayscale inversion viewing methods. METHODS: A random, counterbalanced experimental design was used, where 18 radiologists with varying experiences interpreted the same patient images with and without grayscale inversion. Confirmed positive and negative ELVO cases were randomly ordered using a balanced design. Sensitivity, specificity, positive and negative predictive values as well as confidence, subjective assessment of image quality, time to ELVO detection, and overall interpretation time were examined between grayscale inversion (on/off) by experience level using generalized mixed modeling assuming a binary, negative binomial, and binomial distributions, respectively. RESULTS: All groups of radiologists had high sensitivity and specificity for ELVO detection (all > .94). Neuroradiologists were faster than non-neuroradiologists and residents in interpretation time, with a mean of 47 s to detect ELVO, as compared with 59 and 74 s, respectively. Residents were subjectively less confident than attending physicians. With respect to grayscale inversion, no differences were observed between groups with grayscale inversion vs. standard viewing for diagnostic performance (p = 0.30), detection time (p = .45), overall interpretation time (p = .97), and confidence (p = .20). CONCLUSIONS: Diagnostic performance in ELVO detection with CTA was high across all levels of radiologist training level. Grayscale inversion offered no significant detection advantage. KEY POINTS: • Stroke is an acute vascular syndrome that requires acute vascular imaging. • Proximal large vessel occlusions can be identified quickly and accurately by radiologists across all training levels. • Grayscale inversion demonstrated minimal detectable benefit in the detection of proximal large vessel occlusions.

Interreader Variability of Dynamic Contrast-enhanced MRI of Recurrent Glioblastoma: The Multicenter ACRIN 6677/RTOG 0625 Study.

Purpose To evaluate factors contributing to interreader variation (IRV) in parameters measured at dynamic contrast material-enhanced (DCE) MRI in patients with glioblastoma who were participating in a multicenter trial. Materials and Methods A total of 18 patients (mean age, 57 years ± 13 [standard deviation]; 10 men) who volunteered for the advanced imaging arm of ACRIN 6677, a substudy of the RTOG 0625 clinical trial for recurrent glioblastoma treatment, underwent analyzable DCE MRI at one of four centers. The 78 imaging studies were analyzed centrally to derive the volume transfer constant (Ktrans) for gadolinium between blood plasma and tissue extravascular extracellular space, fractional volume of the extracellular extravascular space (ve), and initial area under the gadolinium concentration curve (IAUGC). Two independently trained teams consisting of a neuroradiologist and a technologist segmented the enhancing tumor on three-dimensional spoiled gradient-recalled acquisition in the steady-state images. Mean and median parameter values in the enhancing tumor were extracted after registering segmentations to parameter maps. The effect of imaging time relative to treatment, map quality, imager magnet and sequence, average tumor volume, and reader variability in tumor volume on IRV was studied by using intraclass correlation coefficients (ICCs) and linear mixed models. Results Mean interreader variations (± standard deviation) (difference as a percentage of the mean) for mean and median IAUGC, mean and median Ktrans, and median ve were 18% ± 24, 17% ± 23, 27% ± 34, 16% ± 27, and 27% ± 34, respectively. ICCs for these metrics ranged from 0.90 to 1.0 for baseline and from 0.48 to 0.76 for posttreatment examinations. Variability in reader-derived tumor volume was significantly related to IRV for all parameters. Conclusion Differences in reader tumor segmentations are a significant source of interreader variation for all dynamic contrast-enhanced MRI parameters. © RSNA, 2018 Online supplemental material is available for this article. See also the editorial by Wolf in this issue.

Pseudoprogression, radionecrosis, inflammation or true tumor progression? challenges associated with glioblastoma response assessment in an evolving therapeutic landscape.

The wide variety of treatment options that exist for glioblastoma, including surgery, ionizing radiation, anti-neoplastic chemotherapies, anti-angiogenic therapies, and active or passive immunotherapies, all may alter aspects of vascular permeability within the tumor and/or normal parenchyma. These alterations manifest as changes in the degree of contrast enhancement or T2-weighted signal hyperintensity on standard anatomic MRI scans, posing a potential challenge for accurate radiographic response assessment for identifying anti-tumor effects. The current review highlights the challenges that remain in differentiating true disease progression from changes due to radiation therapy, including pseudoprogression and radionecrosis, as well as immune or inflammatory changes that may occur as either an undesired result of cytotoxic therapy or as a desired consequence of immunotherapies.

Bidirectional Contrast agent leakage correction of dynamic susceptibility contrast (DSC)-MRI improves cerebral blood volume estimation and survival prediction in recurrent glioblastoma treated with bevacizumab.

PURPOSE: To evaluate a leakage correction algorithm for T1 and T2* artifacts arising from contrast agent extravasation in dynamic susceptibility contrast magnetic resonance imaging (DSC-MRI) that accounts for bidirectional contrast agent flux and compare relative cerebral blood volume (CBV) estimates and overall survival (OS) stratification from this model to those made with the unidirectional and uncorrected models in patients with recurrent glioblastoma (GBM). MATERIALS AND METHODS: We determined median rCBV within contrast-enhancing tumor before and after bevacizumab treatment in patients (75 scans on 1.5T, 19 scans on 3.0T) with recurrent GBM without leakage correction and with application of the unidirectional and bidirectional leakage correction algorithms to determine whether rCBV stratifies OS. RESULTS: Decreased post-bevacizumab rCBV from baseline using the bidirectional leakage correction algorithm significantly correlated with longer OS (Cox, P = 0.01), whereas rCBV change using the unidirectional model (P = 0.43) or the uncorrected rCBV values (P = 0.28) did not. Estimates of rCBV computed with the two leakage correction algorithms differed on average by 14.9%. CONCLUSION: Accounting for T1 and T2* leakage contamination in DSC-MRI using a two-compartment, bidirectional rather than unidirectional exchange model might improve post-bevacizumab survival stratification in patients with recurrent GBM. J. Magn. Reson. Imaging 2016;44:1229-1237.

Management of Craniosynostosis at an Advanced Age: Controversies, Clinical Findings, and Surgical Treatment.

BACKGROUND: The natural history of unrepaired craniosynostosis is not well defined. Delayed surgical intervention carries greater risk of postoperative complications and its functional benefits for older patients are poorly characterized. The authors reviewed patients in whom children presented beyond 1 year of age to better understand the natural history of craniosynostosis, and the risk-benefit relationship for delayed reconstruction. METHODS: After institutional IRB approval the authors conducted a retrospective review of patients who presented after 1 year of age with craniosynostosis. Type of craniosynostosis, age at evaluation, medical history, surgical findings, developmental abnormalities, ophthalmologic findings, and clinical course were reviewed. RESULTS: Ten patients with delayed presentation for craniosynostosis were identified. The mean age at presentation was 6.8 years ±â€Š4.2 years (range, 3-17 years). Seven of 10 patients presented with developmental delay. Five patients presented with debilitating headaches. Five patients presented with comorbid Chiari malformations, 3 of whom required surgical decompression. Two patients had papilledema. Four patients underwent intracranial pressure monitoring, with elevated pressures found in 3 patients. Six patients underwent delayed cranial vault remodeling. There were no peri- or postoperative complications, including infection or residual bony defects, in those undergoing delayed operation. CONCLUSIONS: Children who present in a delayed fashion with unrepaired craniosynostosis have high rates of debilitating headaches, developmental delays, head shape anomalies, and Chiari malformation. Five patients reporting preoperative headaches noted subjective improvements in headaches following delayed operation. Cranial reconstruction can be safely performed at an older age and is appropriate to consider in carefully selected patients for aesthetic and/or functional concerns.

Principles of T2 *-weighted dynamic susceptibility contrast MRI technique in brain tumor imaging.

Dynamic susceptibility contrast magnetic resonance imaging (DSC-MRI) is used to track the first pass of an exogenous, paramagnetic, nondiffusible contrast agent through brain tissue, and has emerged as a powerful tool in the characterization of brain tumor hemodynamics. DSC-MRI parameters can be helpful in many aspects, including tumor grading, prediction of treatment response, likelihood of malignant transformation, discrimination between tumor recurrence and radiation necrosis, and differentiation between true early progression and pseudoprogression. This review aims to provide a conceptual overview of the underlying principles of DSC-MRI of the brain for clinical neuroradiologists, scientists, or students wishing to improve their understanding of the technical aspects, pitfalls, and controversies of DSC perfusion MRI of the brain. Future consensus on image acquisition parameters and postprocessing of DSC-MRI will most likely allow this technique to be evaluated and used in high-quality multicenter studies and ultimately help guide clinical care.

Identification of a single-dose, low flip angle based CBV threshold for fractional tumor burden (FTB) mapping in recurrent glioblastoma.

BACKGROUND AND PURPOSE: DSC-MRI can be used to generate fractional tumor burden (FTB) maps, via application of relative CBV thresholds, to spatially differentiate glioblastoma recurrence from post treatment radiation effects (PTRE). Image-localized histopathology was previously used to validate FTB maps derived from a reference DSC-MRI protocol using preload, a moderate flip angle (MFA, 60°) and post-processing leakage correction. Recently, a DSC-MRI protocol with a low flip angle (LFA, 30°) with no preload was shown to provide leakage-corrected RCBV equivalent to the reference protocol. This study aims to identify the RCBV thresholds for the LFA protocol that generate the most accurate FTB maps, concordant with those obtained from the reference MFA protocol. MATERIALS AND METHODS: Fifty-two patients with grade IV GBM who had prior surgical resection and received chemotherapy and radiotherapy were included in the study. Two sets of DSC-MRI data were collected sequentially first using LFA protocol with no preload, which served as the preload for the subsequent MFA protocol. Standardized relative CBV maps (sRCBV) were obtained for each patient and co-registered with the anatomical post-contrast T1-weighted images. The reference MFA-based FTB maps were computed using previously published sRCBV thresholds (1.0 and 1.56). An ROC analysis was conducted to identify the optimal, voxelwise LFA sRCBV thresholds, and the sensitivity, specificity, and accuracy of the LFA-based FTB maps were computed with respect to the MFA-based reference. RESULTS: The mean sRCBV values of tumors across patients exhibited strong agreement (CCC = 0.99) between the two protocols. Using the ROC analysis, the optimal lower LFA threshold that accurately distinguishes PTRE from tumor recurrence was found to be 1.0 (sensitivity: 87.77%; specificity: 90.22%), equivalent to the ground truth. To identify aggressive tumor regions, the ROC analysis identified an upper LFA threshold of 1.37 (sensitivity: 90.87%; specificity: 91.10%) for the reference MFA threshold of 1.56. CONCLUSION: For LFA-based FTB maps, a sRCBV threshold of 1.0 and 1.37 can differentiate PTRE from recurrent tumor. FTB maps aids in surgical planning, guiding pathological diagnosis and treatment strategies in the recurrent setting. This study further confirms the reliability of single-dose LFA-based DSC-MRI. ABBREVIATIONS: LFA = low flip angle; MFA = moderate flip angle; sRCBV = standardized relative cerebral blood volume; FTB = fractional tumor burden; PTRE = post treatment radiation effects; ROC = receiver operating characteristics; CCC = concordance correlation coefficient.

MRI-Based Prediction of Clinical Improvement Following Ventricular Shunt Placement for Normal Pressure Hydrocephalus (NPH): Development and Evaluation of an Integrated Multi-Sequence Machine Learning Algorithm.

BACKGROUND AND PURPOSE: Symptoms of normal pressure hydrocephalus (NPH) are sometimes refractory to shunt placement, with limited ability to predict improvement for individual patients. We evaluated an MRI-based artificial intelligence method to predict post-shunt NPH symptom improvement. MATERIALS AND METHODS: NPH patients who underwent magnetic resonance imaging (MRI) prior to shunt placement at a single center (2014-2021) were identified. Twelve-month post-shunt improvement in modified Rankin Scale (mRS), incontinence, gait, and cognition were retrospectively abstracted from clinical documentation. 3D deep residual neural networks were built on skull stripped T2-weighted and fluid attenuated inversion recovery (FLAIR) images. Predictions based on both sequences were fused by additional network layers. Patients from 2014-2019 were used for parameter optimization, while those from 2020-2021 were used for testing. Models were validated on an external validation dataset from a second institution (n=33). RESULTS: Of 249 patients, n=201 and n=185 were included in the T2-based and FLAIR-based models according to imaging availability. The combination of T2-weighted and FLAIR sequences offered the best performance in mRS and gait improvement predictions relative to models trained on imaging acquired using only one sequence, with AUROC values of 0.7395 [0.5765-0.9024] for mRS and 0.8816 [0.8030-0.9602] for gait. For urinary incontinence and cognition, combined model performances on predicting outcomes were similar to FLAIR-only performance, with AUROC values of 0.7874 [0.6845-0.8903] and 0.7230 [0.5600-0.8859]. CONCLUSIONS: Application of a combined algorithm using both T2-weighted and FLAIR sequences offered the best image-based prediction of post-shunt symptom improvement, particularly for gait and overall function in terms of mRS. ABBREVIATIONS: NPH = normal pressure hydrocephalus; iNPH = idiopathic NPH; sNPH = secondary NPH; AI = artificial intelligence; ML = machine learning; CSF = cerebrospinal fluid; AUROC = area under the receiver operating characteristic; FLAIR = fluid attenuated inversion recovery; BMI = body mass index; CCI = Charlson Comorbidity Index; SD = standard deviation; IQR = interquartile range.

A Neuroradiologist's Guide to Operationalizing the Response Assessment in Neuro-Oncology (RANO) Criteria Version 2.0 for Gliomas in Adults.

Radiographic assessment plays a crucial role in the management of patients with central nervous system (CNS) tumors, aiding in treatment planning and evaluation of therapeutic efficacy by quantifying response. Recently, an updated version of the Response Assessment in Neuro-Oncology (RANO) criteria (RANO 2.0) was developed to improve upon prior criteria and provide an updated, standardized framework for assessing treatment response in clinical trials for gliomas in adults. This article provides an overview of significant updates to the criteria including (1) the use of a unified set of criteria for high and low grade gliomas in adults; (2) the use of the post-radiotherapy MRI scan as the baseline for evaluation in newly diagnosed high-grade gliomas; (3) the option for the trial to mandate a confirmation scan to more reliably distinguish pseudoprogression from tumor progression; (4) the option of using volumetric tumor measurements; and (5) the removal of subjective non-enhancing tumor evaluations in predominantly enhancing gliomas (except for specific therapeutic modalities). Step-by-step pragmatic guidance is hereby provided for the neuroradiologist and imaging core lab involved in operationalization and technical execution of RANO 2.0 in clinical trials, including the display of representative cases and in-depth discussion of challenging scenarios.ABBREVIATIONS: BTIP = Brain Tumor Imaging Protocol; CE = Contrast-Enhancing; CNS = Central Nervous System; CR = Complete Response; ECOG = Eastern Cooperative Oncology Group; HGG = High-Grade Glioma; IDH = Isocitrate Dehydrogenase; IRF = Independent Radiologic Facility; LGG = Low-Grade Glioma; KPS = Karnofsky Performance Status; MR = Minor Response; mRANO = Modified RANO; NANO = Neurological Assessment in Neuro-Oncology; ORR = Objective Response Rate; OS = Overall Survival; PD = Progressive Disease; PFS = Progression-Free Survival; PR = Partial Response; PsP = Pseudoprogression; RANO = Response Assessment in Neuro-Oncology; RECIST = Response Evaluation Criteria In Solid Tumors; RT = Radiation Therapy; SD = Stable Disease; Tx = Treatment.

Prenatal MRI characterization of brainstem glioma.

We describe a unique case of prenatally diagnosed diffuse brainstem glioma, detected during routine obstetric ultrasound and characterized with fetal magnetic resonance imaging. The diagnosis was supported by early postpartum imaging and confirmed at autopsy. Few examples of these rare lesions have been described in neonates by imaging and fewer cases have been confirmed by histopathological examination. Our case contributes to the limited literature concerning the clinical, MRI, and pathological correlates of brainstem gliomas in the perinatal period.

Advances in myelin imaging with potential clinical application to pediatric imaging.

White matter development and myelination are critical processes in neurodevelopment. Myelinated white matter facilitates the rapid and coordinated brain messaging required for higher-order cognitive and behavioral processing. Whereas several neurological disorders such as multiple sclerosis are associated with gross white matter damage and demyelination, other disorders such as epilepsy may involve altered myelination in the efferent or afferent white matter pathways adjoining epileptic foci. Current MRI techniques including T1 weighting, T2 weighting, FLAIR, diffusion tensor imaging, and MR spectroscopy permit visualization of gross white matter abnormalities and evaluation of underlying white matter fiber architecture and integrity, but they provide only qualitative information regarding myelin content. Quantification of these myelin changes could provide new insight into disease severity and prognosis, reveal information regarding spatial location of foci or lesions and the associated affected neural systems, and create a metric to evaluate treatment efficacy. Multicomponent analysis of T1 and T2 relaxation data, or multicomponent relaxometry (MCR), is a quantitative imaging technique that is sensitive and specific to myelin content alteration. In the past, MCR has been associated with lengthy imaging times, but a new, faster MCR technique (mcDESPOT) has made quantitative analysis of myelin content more accessible for clinical research applications. The authors briefly summarize traditional white matter imaging techniques, describe MCR and mcDESPOT, and discuss current and future clinical applications of MCR, with a particular focus on pediatric epilepsy.

Early post-bevacizumab change in rCBV from DSC-MRI identifies pseudoresponse in recurrent glioblastoma: Results from ACRIN 6677/RTOG 0625.

Background: Progressive enhancement predicted poor survival in ACRIN 6677/RTOG 0625, a multi-center trial of bevacizumab with irinotecan or temozolomide in recurrent glioblastoma, but pseudoresponse likely limited enhancement-based survival prognostication in T1 non-progressors. We aimed to determine whether early change in cerebral blood volume from baseline (ΔCBV) could further stratify the T1 non-progressors according to overall (OS) and progression-free (PFS) survival. Methods: 37/123 enrolled patients had DSC-MRI, including 13, 15, and 8 patients without 2D-T1 progression at 2, 8, and 16 weeks post-treatment initiation, respectively. Mean CBV normalized to white matter (nRCBV) and mean standardized CBV (sRCBV) were extracted from enhancing tumor. ROC curves were derived for ΔCBV using six-month PFS and one-year OS as reference standards. Kaplan-Meier survival estimates and log-rank test compared PFS and OS for both ΔCBV (increase vs. decrease) and T1 response status (stable vs. decreasing enhancement). Results: PFS and OS were significantly worse for increasing CBV at 2 weeks (p=0.003 and p=0.002 for nRCBV, and p=0.03 and p=0.03 for sRCBV, respectively), but not for 2D-T1 patients with stable vs. decreasing enhancement (p=0.44 and p=0.86, respectively). ΔCBV at week 2 was also a good prognostic marker for OS-1 and PFS-6 using ROC analysis. By contrast, 2D-T1 response status at weeks 2, 8, and 16 was not associated with PFS-6. ΔCBV at 16 weeks (p=0.008 for sRCBV) but not 8 weeks (p=0.74 for nRCBV and p=0.56 for sRCBV) was associated with significant difference in median survival, but no difference in survival was observed for 2D-T1 patients with stable vs. decreasing enhancement at 8 weeks (p=0.69) or 16 weeks (p=0.21). At 16 weeks, OS did not differ significantly between 2D-T1 progressors and 2D-T1 non-progressors with increasing CBV (median survival 3.3 months post week 16 scan vs. 9.2 months, respectively; p=0.13), suggesting that 2D-T1 non-progressors with increasing CBV may have a prognosis like that of 2D-T1 progressors. Conclusion: After 2 weeks of anti-angiogenic therapy, ΔCBV in 2D-T1 non-progressors significantly prognosticated PFS and OS, whereas 2D-T1 response status did not, identifying a subpopulation that benefits from bevacizumab. Combining 2D-T1 progression and ΔCBV may yield a response assessment paradigm with 3-tiered OS stratification.

A cross-sectional study to test equivalence of low- versus intermediate-flip angle dynamic susceptibility contrast MRI measures of relative cerebral blood volume in patients with high-grade gliomas at 1.5 Tesla field strength.

Introduction: 1.5 Tesla (1.5T) remain a significant field strength for brain imaging worldwide. Recent computer simulations and clinical studies at 3T MRI have suggested that dynamic susceptibility contrast (DSC) MRI using a 30° flip angle ("low-FA") with model-based leakage correction and no gadolinium-based contrast agent (GBCA) preload provides equivalent relative cerebral blood volume (rCBV) measurements to the reference-standard acquisition using a single-dose GBCA preload with a 60° flip angle ("intermediate-FA") and model-based leakage correction. However, it remains unclear whether this holds true at 1.5T. The purpose of this study was to test this at 1.5T in human high-grade glioma (HGG) patients. Methods: This was a single-institution cross-sectional study of patients who had undergone 1.5T MRI for HGG. DSC-MRI consisted of gradient-echo echo-planar imaging (GRE-EPI) with a low-FA without preload (30°/P-); this then subsequently served as a preload for the standard intermediate-FA acquisition (60°/P+). Both normalized (nrCBV) and standardized relative cerebral blood volumes (srCBV) were calculated using model-based leakage correction (C+) with IBNeuro™ software. Whole-enhancing lesion mean and median nrCBV and srCBV from the low- and intermediate-FA methods were compared using the Pearson's, Spearman's and intraclass correlation coefficients (ICC). Results: Twenty-three HGG patients composing a total of 31 scans were analyzed. The Pearson and Spearman correlations and ICCs between the 30°/P-/C+ and 60°/P+/C+ acquisitions demonstrated high correlations for both mean and median nrCBV and srCBV. Conclusion: Our study provides preliminary evidence that for HGG patients at 1.5T MRI, a low FA, no preload DSC-MRI acquisition can be an appealing alternative to the reference standard higher FA acquisition that utilizes a preload.

Advanced MRI Protocols to Discriminate Glioma From Treatment Effects: State of the Art and Future Directions.

In the follow-up treatment of high-grade gliomas (HGGs), differentiating true tumor progression from treatment-related effects, such as pseudoprogression and radiation necrosis, presents an ongoing clinical challenge. Conventional MRI with and without intravenous contrast serves as the clinical benchmark for the posttreatment surveillance imaging of HGG. However, many advanced imaging techniques have shown promise in helping better delineate the findings in indeterminate scenarios, as posttreatment effects can often mimic true tumor progression on conventional imaging. These challenges are further confounded by the histologic admixture that can commonly occur between tumor growth and treatment-related effects within the posttreatment bed. This review discusses the current practices in the surveillance imaging of HGG and the role of advanced imaging techniques, including perfusion MRI and metabolic MRI.

Deep learning-based automatic tumor burden assessment of pediatric high-grade gliomas, medulloblastomas, and other leptomeningeal seeding tumors.

BACKGROUND: Longitudinal measurement of tumor burden with magnetic resonance imaging (MRI) is an essential component of response assessment in pediatric brain tumors. We developed a fully automated pipeline for the segmentation of tumors in pediatric high-grade gliomas, medulloblastomas, and leptomeningeal seeding tumors. We further developed an algorithm for automatic 2D and volumetric size measurement of tumors. METHODS: The preoperative and postoperative cohorts were randomly split into training and testing sets in a 4:1 ratio. A 3D U-Net neural network was trained to automatically segment the tumor on T1 contrast-enhanced and T2/FLAIR images. The product of the maximum bidimensional diameters according to the RAPNO (Response Assessment in Pediatric Neuro-Oncology) criteria (AutoRAPNO) was determined. Performance was compared to that of 2 expert human raters who performed assessments independently. Volumetric measurements of predicted and expert segmentations were computationally derived and compared. RESULTS: A total of 794 preoperative MRIs from 794 patients and 1003 postoperative MRIs from 122 patients were included. There was excellent agreement of volumes between preoperative and postoperative predicted and manual segmentations, with intraclass correlation coefficients (ICCs) of 0.912 and 0.960 for the 2 preoperative and 0.947 and 0.896 for the 2 postoperative models. There was high agreement between AutoRAPNO scores on predicted segmentations and manually calculated scores based on manual segmentations (Rater 2 ICC = 0.909; Rater 3 ICC = 0.851). Lastly, the performance of AutoRAPNO was superior in repeatability to that of human raters for MRIs with multiple lesions. CONCLUSIONS: Our automated deep learning pipeline demonstrates potential utility for response assessment in pediatric brain tumors. The tool should be further validated in prospective studies.

Cortical blindness following a near-drowning incident.

Victims of near-drowning incidents often suffer neurologic injury with long-term sequelae secondary to hypoxic-ischemic injury. We describe a case of profound visual loss due to bilateral occipital lobe infarcts in a 23-year-old male victim of a near-drowning incident.

The relationship between cerebral and retinal microbleeds in cerebral amyloid angiopathy (CAA): A pilot study.

BACKGROUND: The standard in vivo diagnostic imaging technique for cerebral amyloid angiopathy (CAA) is costly and thereby of limited utility for point-of-care diagnosis and monitoring of treatment efficacy. Recent recognition that retinal changes may reflect cerebral changes in neurodegenerative disease provides an ideal opportunity for development of accessible and cost-effective biomarkers for point-of-care use in the detection and monitoring of CAA. In this pilot study, we examined structural and angiographic retinal changes in CAA patients relative to a control group, and compared retinal and cerebral pathology in a group of CAA patients. METHODS: We used spectral domain optical coherence tomography (SD-OCT) to image the retina and compared retinal microbleeds to both cerebral microbleeds and white matter hyperintensities (WMH) in CAA patients, as seen on MRI. We compared retinal angiographic changes, along with structural retinal neuronal layer changes in CAA patients and cognitively normal older adults, and examined the relationship between retinal and cerebral microbleeds and cognition in CAA patients. RESULTS: We found a trend level correlation between retinal and cerebral microbleeds in CAA patients. Moreover, we found a significant correlation between retinal microbleeds and episodic memory performance in CAA patients. There were no significant group differences between CAA patients and cognitively normal older adults on retinal angiographic or structural measurements. CONCLUSION: Retinal microbleeds may reflect degree of cerebral microbleed burden in CAA. This picture was complicated by systolic hypertension in the CAA group, which is a confounding factor for the interpretation of these data. Our results stimulate motivation for pursuit of a more comprehensive prospective study to determine the feasibility of retinal biomarkers in CAA.

Value of dynamic contrast perfusion MRI to predict early response to bevacizumab in newly diagnosed glioblastoma: results from ACRIN 6686 multicenter trial.

BACKGROUND: In Radiation Therapy Oncology Group (RTOG) 0825, a phase III trial of standard therapy with bevacizumab or without (placebo) in newly diagnosed glioblastoma, 44 patients underwent dynamic contrast enhanced (DCE) and/or dynamic susceptibility contrast (DSC) MRI in the American College of Radiology Imaging Network (ACRIN) trial 6686. The association between early changes in relative cerebral blood volume (rCBV) and volume transfer constant (Ktrans) with overall survival (OS) was evaluated. METHODS: MRI was performed at postop baseline (S0), immediately before (S1), 1 day after (S2), and 7 weeks after (S3) bevacizumab or placebo initiation. Mean normalized and standardized rCBV (nRCBV, sRCBV) and Ktrans were measured within contrast-enhancing lesion. Wilcoxon rank sum tests compared parameter changes from S1-S2 and S1-S3. Association with OS and progression-free survival (PFS) were determined using Kaplan-Meier and log-rank tests. Treatment response for groups stratified by pretreatment nRCBV (S0, S1) was explored. The intraclass correlation coefficient and repeatability coefficient for the placebo arm (S1-S2) were used to assess repeatability. RESULTS: Evaluable were 27-36 datasets per time point. Significant differences between treatment arms were found for changes in nRCBV and sRCBV from S1-S2 and S1-S3, and in Ktrans for S1-S3. Improved PFS (P = 0.05) but not OS (P = 0.46) was observed. High pretreatment rCBV predicted improved OS for bevacizumab-treated patients. Based on the intraclass correlation coefficient, sRCBV (0.92) was more repeatable than nRCBV (0.71) and Ktrans (0.75), consistent with repeatability coefficient values. CONCLUSIONS: Bevacizumab significantly changes rCBV but not Ktrans as early as 1 day posttreatment in newly diagnosed glioblastoma unrelated to outcomes. Improvements in clinical trial design to maximize rCBV benefit are indicated.