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Background The coronavirus disease 2019 (COVID-19) pandemic has significantly impacted outpatient radiology practices, necessitating change in practice infrastructure and workflow. Objective The purpose of this study was to assess the consequences of social distancing regulations on 1) outpatient imaging volume and 2) no-show rates per imaging modality. Methods Volume and no-show rates of a large, multicenter metropolitan healthcare system outpatient practice were retrospectively stratified by modality including radiography, CT, MRI, ultrasonography, PET, DEXA, and mammography from January 2 to July 21, 2020. Trends were assessed relative to timepoints of significant state and local social distancing regulatory changes. Results The decline in imaging volume and rise in no-show rates was first noted on March 10, 2020 following the declaration of a state of emergency in New York State (NYS). Total outpatient imaging volume declined 85% from baseline over the following 5 days. Decreases varied by modality: 88% for radiography, 75% for CT, 73% for MR, 61% for PET, 80% for ultrasonography, 90% for DEXA, and 85% for mammography. Imaging volume and no-show rate recovery preceded the mask mandate of April 15, 2020, and further trended along with New York City's reopening phases. No-show rates recovered within 2 months of the height of the pandemic, however, outpatient imaging volume has yet to recover to baseline after 3 months. Conclusion The total outpatient imaging volume declined alongside an increase in the no-show rate following the declaration of a state of emergency in NYS. No-show rates recovered within 2 months of the height of the pandemic with imaging volume yet to recover after 3 months. Clinical impact Understanding the impact of social distancing regulations on outpatient imaging volume and no-show rates can potentially aid other outpatient radiology practices and healthcare systems in anticipating upcoming changes as the COVID-19 pandemic evolves.

In the past 2 decades, a deeper understanding of the cancer molecular signature has resulted in longer longevity of cancer patients, hence a greater population, who potentially can develop metastatic disease. Spine metastases (SM) occur in up to 70% of cancer patients. Familiarizing ourselves with the key aspects of initial symptom-directed management is important to provide SM patients with the best patient-specific options. We will review key components of initial symptoms assessment such as pain, neurological symptoms, and spine stability. Radiographic evaluation of SM and its role in management will be reviewed. Nonsurgical treatment options are also presented and discussed, including percutaneous procedures, radiation, radiosurgery, and spine stereotactic body radiotherapy. The efforts of a multidisciplinary team will continue to ensure the best patient care as the landscape of cancer is constantly changing.

Coronavirus disease 2019 (COVID-19), a clinical manifestation of severe acute respiratory syndrome coronavirus-2 (SARS-CoV-2), was declared a global pandemic by the World Health Organization on March 11, 2020. Hypercoagulable state has been described as one of the hallmarks of SARS-CoV-2 infection and has been reported to manifest as pulmonary embolisms, deep vein thrombosis, and arterial thrombosis of the abdominal small vessels. Here we present cases of arterial and venous thrombosis pertaining to the head and neck in COVID-19 patients., Highlights • We present cases: intracranial and extracranial large vessel occlusions, hemorrhagic strokes, and venous sinus thrombosis. • It is important to recognize possible neurovascular complications that can be seen in COVID-19 patients on imaging as early detection and management can contribute to effective response.

BACKGROUND AND PURPOSE: Pathology and microbiology results for suspected spondylodiscitis on MR imaging are often negative in up to 70% of cases. We aimed to predict whether MR imaging features will add diagnostic value when combined with clinical biomarkers to predict positive findings of spondylodiscitis on pathology and/or microbiology from percutaneous biopsy. MATERIALS AND METHODS: In this retrospective single-center institutional review board–approved study, patients with radiologically suspected spondylodiscitis and having undergone percutaneous biopsies were assessed. Demographic characteristics, laboratory values, and tissue and blood cultures were collected. Pathology and microbiology results were used as end points. Three independent observers provided MR imaging–based scoring for typical MR imaging features for spondylodiscitis. Multivariate logistic regression and receiver operating characteristic analysis were performed to determine an optimal combination of imaging and clinical biomarkers in predicting positive findings on pathology and/or microbiology from percutaneous biopsy suggestive of spondylodiscitis. RESULTS: Our patient cohort consisted of 72 patients, of whom 33.3% (24/72) had spondylodiscitis. The mean age was 63 ± 16 years with a male/female ratio of 41:31. Logistic regression revealed a combination with an area under the curve of 0.72 for pathology and 0.68 for pathology and/or microbiology. Epidural enhancement on MR imaging improved predictive performance to 0.87 for pathology and 0.78 for pathology and/or microbiology. CONCLUSIONS: Our findings demonstrate that epidural enhancement on MR imaging added diagnostic value when combined with clinical biomarkers to help predict which patients undergoing percutaneous biopsy will have positive findings for spondylodiscitis on pathology and/or microbiology.

BACKGROUND AND PURPOSE: There is scarcity of data on the comparative efficacy between bone biopsy drill systems across various types of bone lesions. Our aim was to investigate differences in diagnostic yield, scanning time, and radiation dose between manual and battery-powered bone biopsy systems in CT-guided biopsies of lytic, sclerotic, and infectious bone lesions. MATERIALS AND METHODS: This was a retrospective single-center institutional review board–approved study. A total of 585 CT-guided core needle biopsies were performed at 1 institution from May 2010 to February 2019. Classification of bone lesions, location, bone biopsy system, suspected origin of primary disease, final pathologic diagnosis, diagnostic yield, presence of crush artifacts, radiation dose, and scanning times were collected. For the battery-powered system, OnControl was used. For the manual drill system, Bonopty, Osteo-site, and Laurane drill systems were used. Comparisons in lytic and sclerotic lesions and suspected discitis/osteomyelitis were made using the Fisher exact test. Subgroup analysis of the drill systems for scanning time and radiation dose was performed by 1-way ANOVA. RESULTS: Our patient cohorts consisted of a total of 585 patients with 422 lytic, 110 sclerotic, and 53 suspected infectious lesions. The mean age was 62 ± 13 years with a male/female ratio of 305:280 for all lesions. The diagnostic yield was 85.5% (362/422) for lytic, 82.7% (91/110) for sclerotic, 50.9% (27/53) for infectious lesions, and 82.1% (480/585) for all lesions. No statistical difference was found when comparing diagnostic yields of powered drills with the manual systems for lytic, sclerotic, and infectious lesions. However, in a subgroup analysis, radiation dose and scanning time were significantly lower for powered drill compared with manual drill systems in lytic (P = .001 for both) and sclerotic lesions (P = .028 and P = .012, respectively). No significant differences were seen between the drill systems for suspected infectious lesions. CONCLUSIONS: Our findings demonstrate that there was no statistically significant difference in diagnostic yield when comparing battery-powered and manual bone biopsy systems for CT-guided bone biopsies; however, the use of the power drill system resulted in significantly reduced scanning time and radiation dose in lytic and sclerotic lesions.

BACKGROUND AND PURPOSE: Two-thirds of lymphatic malformations in children are found in the head and neck. Although conventionally managed through surgical resection, percutaneous sclerotherapy has gained popularity. No reproducible grading system has been designed to compare sclerotherapy outcomes on the basis of radiologic findings. We propose an MR imaging–based grading scale to assess the response to sclerotherapy and present an evaluation of its interrater reliability. MATERIALS AND METHODS: A grading system was developed to stratify treatment outcomes on the basis of interval changes observed on MR imaging. By means of this system, 56 consecutive cases from our institution with formally diagnosed head and neck lymphatic malformations treated by sclerotherapy were retrospectively graded. Each patient underwent pre- and posttreatment MR imaging. Each study was evaluated by 3 experienced neuroradiologists. Interrater reliability was assessed using the Krippendorff α statistic, intraclass coefficient, and 2-way Spearman ρ correlation. RESULTS: The overall Krippendorff α statistic was 0.93 (95% CI, 0.89–0.95), denoting excellent agreement among raters. Intraclass coefficients with respect to consistency and absolute agreements were both 0.97 (95% CI, 0.96–0.98), illustrating low variability. Every combination of individual rater pairs demonstrated statistically significant (P < .01) linear Spearman ρ correlations, with values ranging from 0.90 to 0.95. CONCLUSIONS: The proposed radiographic grading scale demonstrates excellent interrater reliability. Adoption of this new scale can standardize reported outcomes following sclerotherapy for head and neck lymphatic malformation and may aid in the investigation of future questions regarding optimal management of these lesions.

BackgroundTreated aneurysms must be followed over time to ensure durable occlusion, as more than 20% of endovascularly treated aneurysms recur. While digital subtraction angiography (DSA) remains the gold standard, magnetic resonance angiography (MRA) is attractive as a non-invasive follow-up technique. Two different MRA techniques have traditionally been used: time-of-flight (TOF) and contrast-enhanced (CE) MRA. We analysed data from studies comparing MRA techniques with DSA for the follow-up of aneurysms undergoing endovascular treatment. Subgroup analysis of stent-assisted coiling (SAC) and flow diversion (FD) techniques was completed.MethodsComprehensive searches using the Embase, PubMed, and Cochrane databases were performed and updated to November 2018. Pooled sensitivity and specificity were calculated using aneurysm occlusion status as defined by the Raymond–Roy occlusion grading scale.ResultsThe literature search yielded 1579 unique titles. Forty-three studies were included. For TOF-MRA, sensitivity and specificity of all aneurysms undergoing endovascular therapy were 88% and 94%, respectively. For CE-MRA, the sensitivity and specificity were 88% and 96%, respectively. For SAC and FD techniques, sensitivity and specificity of TOF-MRA were 86% and 95%, respectively. CE-MRA had sensitivity and specificity of 90% and 92%.ConclusionMRA is a reliable modality for the follow-up of aneurysms treated using endovascular techniques. While the data are limited, MRA techniques can also be used to reliably follow patients undergoing FD and SAC. However, clinical factors must be used to optimize follow-up regimens for individual patients.

Most current medical imaging Artificial Intelligence (AI) relies upon transfer learning using convolutional neural networks (CNNs) created using ImageNet, a large database of natural world images, including cats, dogs, and vehicles. Size, diversity, and similarity of the source data determine the success of the transfer learning on the target data. ImageNet is large and diverse, but there is a significant dissimilarity between its natural world images and medical images, leading Cheplygina to pose the question, “Why do we still use images of cats to help Artificial Intelligence interpret CAT scans?”. We present an equally large and diversified database, RadImageNet, consisting of 5 million annotated medical images consisting of CT, MRI, and ultrasound of musculoskeletal, neurologic, oncologic, gastrointestinal, endocrine, and pulmonary pathologies over 450,000 patients. The database is unprecedented in scale and breadth in the medical imaging field, constituting a more appropriate basis for medical imaging transfer learning applications. We found that RadImageNet transfer learning outperformed ImageNet in multiple independent applications, including improvements for bone age prediction from hand and wrist x-rays by 1.75 months (p

With the rapid growth and increasing use of brain MRI, there is an interest in automated image classification to aid human interpretation and improve workflow. We aimed to train a deep convolutional neural network and assess its performance in identifying abnormal brain MRIs and critical intracranial findings including acute infarction, acute hemorrhage and mass effect. A total of 13,215 clinical brain MRI studies were categorized to training (74%), validation (9%), internal testing (8%) and external testing (8%) datasets. Up to eight contrasts were included from each brain MRI and each image volume was reformatted to common resolution to accommodate for differences between scanners. Following reviewing the radiology reports, three neuroradiologists assigned each study to abnormal vs normal, and identified three critical findings including acute infarction, acute hemorrhage, and mass effect. A deep convolutional neural network was constructed by a combination of localization feature extraction (LFE) modules and global classifiers to identify the presence of 4 variables in brain MRIs including abnormal, acute infarction, acute hemorrhage and mass effect. Training, validation and testing sets were randomly defined on a patient basis. Training was performed on 9845 studies using balanced sampling to address class imbalance. Receiver operating characteristic (ROC) analysis was performed. The ROC analysis of our models for 1050 studies within our internal test data showed AUC/sensitivity/specificity of 0.91/83%/86% for normal versus abnormal brain MRI, 0.95/92%/88% for acute infarction, 0.90/89%/81% for acute hemorrhage, and 0.93/93%/85% for mass effect. For 1072 studies within our external test data, it showed AUC/sensitivity/specificity of 0.88/80%/80% for normal versus abnormal brain MRI, 0.97/90%/97% for acute infarction, 0.83/72%/88% for acute hemorrhage, and 0.87/79%/81% for mass effect. Our proposed deep convolutional network can accurately identify abnormal and critical intracranial findings on individual brain MRIs, while addressing the fact that some MR contrasts might not be available in individual studies.

Background and Purpose: Randomized controlled trials have demonstrated the importance of time to endovascular therapy (EVT) on clinical outcomes in large vessel occlusion (LVO) acute ischemic stroke. Delays to treatment are particularly prevalent when patients require a transfer from hospitals without EVT capability onsite. A novel computer aided triage system, Viz LVO, has the potential to streamline workflows. This platform includes an image viewer, communication system, and an artificial intelligence (AI) algorithm that automatically identifies suspected LVO strokes on CTA imaging and rapidly triggers alerts. We hypothesize that the Viz application will decrease time-to-treatment. Methods: A prospective database was assessed for patients who presented to a stroke center utilizing Viz LVO in the Mount Sinai Health System in New York and underwent EVT following transfer for LVO stroke between July 2018 and March 2020. This time period was chosen due to the COVID-19 pandemic affecting stroke workflow after March 2020. Time intervals were compared for 55 patients divided into Pre- and Post-Viz cohorts. Results: The median initial door-to-neuroendovascular team (NT) notification time interval was significantly faster (25.0 minutes [IQR=12.0] vs 40.0 minutes [IQR=61.0]; p=0.01) with significantly less variation (p Conclusions: Our preliminary results have shown that Viz LVO implementation is associated with earlier, more consistent NT notification times and potentially treatment times. This platform presents a novel application of AI that can serve as an early warning system and a failsafe to ensure that no LVO is left behind. Further studies are warranted.

Highlights • The attention mechanism can rank MR measures by relative importance. • Proposed guideline for use of the attention mechanism with MR measures. • Attention weights and quantitative MR measures can potentially form new patterns., Introduction During the last decade, a multitude of novel quantitative and semiquantitative MRI techniques have provided new information about the pathophysiology of neurological diseases. Yet, selection of the most relevant contrasts for a given pathology remains challenging. In this work, we developed and validated a method, Gated-Attention MEchanism Ranking of multi-contrast MRI in brain pathology (GAMER MRI), to rank the relative importance of MR measures in the classification of well understood ischemic stroke lesions. Subsequently, we applied this method to the classification of multiple sclerosis (MS) lesions, where the relative importance of MR measures is less understood. Methods GAMER MRI was developed based on the gated attention mechanism, which computes attention weights (AWs) as proxies of importance of hidden features in the classification. In the first two experiments, we used Trace-weighted (Trace), apparent diffusion coefficient (ADC), Fluid-Attenuated Inversion Recovery (FLAIR), and T1-weighted (T1w) images acquired in 904 acute/subacute ischemic stroke patients and in 6,230 healthy controls and patients with other brain pathologies to assess if GAMER MRI could produce clinically meaningful importance orders in two different classification scenarios. In the first experiment, GAMER MRI with a pretrained convolutional neural network (CNN) was used in conjunction with Trace, ADC, and FLAIR to distinguish patients with ischemic stroke from those with other pathologies and healthy controls. In the second experiment, GAMER MRI with a patch-based CNN used Trace, ADC and T1w to differentiate acute ischemic stroke lesions from healthy tissue. The last experiment explored the performance of patch-based CNN with GAMER MRI in ranking the importance of quantitative MRI measures to distinguish two groups of lesions with different pathological characteristics and unknown quantitative MR features. Specifically, GAMER MRI was applied to assess the relative importance of the myelin water fraction (MWF), quantitative susceptibility mapping (QSM), T1 relaxometry map (qT1), and neurite density index (NDI) in distinguishing 750 juxtacortical lesions from 242 periventricular lesions in 47 MS patients. Pair-wise permutation t-tests were used to evaluate the differences between the AWs obtained for each quantitative measure. Results In the first experiment, we achieved a mean test AUC of 0.881 and the obtained AWs of FLAIR and the sum of AWs of Trace and ADC were 0.11 and 0.89, respectively, as expected based on previous knowledge. In the second experiment, we achieved a mean test F1 score of 0.895 and a mean AW of Trace = 0.49, of ADC = 0.28, and of T1w = 0.23, thereby confirming the findings of the first experiment. In the third experiment, MS lesion classification achieved test balanced accuracy = 0.777, sensitivity = 0.739, and specificity = 0.814. The mean AWs of T1map, MWF, NDI, and QSM were 0.29, 0.26, 0.24, and 0.22 (p

Rationale and Objectives This study seeks to quantify the financial impact of COVID-19 on radiology departments, and to describe the structure of both volume and revenue recovery. Materials and Methods Radiology studies from a large academic health system were retrospectively studied from the first 33 weeks of 2020. Volume and work relative value unit (wRVU) data were aggregated on a weekly basis for three periods: Presurge (weeks 1–9), surge (10–19), and recovery (20–33), and analyzed compared to the pre-COVID baseline stratified by modality, specialty, patient service location, and facility type. Mean and median wRVU per study were used as a surrogate for case complexity. Results During the pandemic surge, case volumes fell 57%, while wRVUs fell by 69% relative to the pre-COVID-19 baseline. Mean wRVU per study was 1.13 in the presurge period, 1.03 during the surge, and 1.19 in the recovery. Categories with the greatest mean complexity declines were radiography (−14.7%), cardiothoracic imaging (−16.2%), and community hospitals overall (−15.9%). Breast imaging (+6.5%), interventional (+5.5%), and outpatient (+12.1%) complexity increased. During the recovery, significant increases in complexity were seen in cardiothoracic (0.46 to 0.49), abdominal (1.80 to 1.91), and neuroradiology (2.46 to 2.56) at stand-alone outpatient centers with similar changes at community hospitals. At academic hospitals, only breast imaging complexity remained elevated (1.32 from 1.17) during the recovery. Conclusion Reliance on volume alone underestimates the financial impact of the COVID-19 pandemic as there was a disproportionate loss in high-RVU studies. However, increased complexity of outpatient cases has stabilized overall losses during the recovery.

Sacral insufficiency fractures (SIF) require prompt intervention, as they are associated with high morbidity and worsened quality of life. Standard of care currently involves a multimodal approach of rehabilitation and pharmacological therapies. However, these measures may not provide significant pain relief and pose additional risks relating to prolonged immobility and analgesic dependence. Sacroplasty is a minimally invasive imaging-guided alternative to conservative management in the treatment of SIF. This procedure involves the injection of polymethyl methacrylate (PMMA) cement under guidance of computed tomography and/or fluoroscopy to reinforce the stability and durability of SIF. Sacroplasty is associated with rapid pain relief, improvement of functional status, and decreased analgesic use. Complications, most commonly cement extravasation, are few and generally clinically insignificant.

Study design Cross-sectional database study. Objective The objective of this study was to develop an algorithm for the automated measurement of spinopelvic parameters on lateral lumbar radiographs with comparable accuracy to surgeons. Summary of background data Sagittal alignment measurements are important for the evaluation of spinal disorders. Manual measurement methods are time-consuming and subject to rater-dependent error. Thus, a need exists to develop automated methods for obtaining sagittal measurements. Previous studies of automated measurement have been limited in accuracy, inapplicable to common plain films, or unable to measure pelvic parameters. Methods Images from 816 patients receiving lateral lumbar radiographs were collected sequentially and used to develop a convolutional neural network (CNN) segmentation algorithm. A total of 653 (80%) of these radiographs were used to train and validate the CNN. This CNN was combined with a computer vision algorithm to create a pipeline for the fully automated measurement of spinopelvic parameters from lateral lumbar radiographs. The remaining 163 (20%) of radiographs were used to test this pipeline. Forty radiographs were selected from the test set and manually measured by three surgeons for comparison. Results The CNN achieved an area under the receiver-operating curve of 0.956. Algorithm measurements of L1-S1 cobb angle, pelvic incidence, pelvic tilt, and sacral slope were not significantly different from surgeon measurement. In comparison to criterion standard measurement, the algorithm performed with a similar mean absolute difference to spine surgeons for L1-S1 Cobb angle (4.30° ± 4.14° vs. 4.99° ± 5.34°), pelvic tilt (2.14° ± 6.29° vs. 1.58° ± 5.97°), pelvic incidence (4.56° ± 5.40° vs. 3.74° ± 2.89°), and sacral slope (4.76° ± 6.93° vs. 4.75° ± 5.71°). Conclusion This algorithm measures spinopelvic parameters on lateral lumbar radiographs with comparable accuracy to surgeons. The algorithm could be used to streamline clinical workflow or perform large scale studies of spinopelvic parameters.Level of Evidence: 3.

Background and Purpose: Randomized controlled trials have demonstrated the importance of time to endovascular therapy (EVT) in clinical outcomes in large vessel occlusion (LVO) acute ischemic stroke. Delays to treatment are particularly prevalent when patients require a transfer from hospitals without EVT capability onsite. A computer-aided triage system, Viz LVO, has the potential to streamline workflows. This platform includes an image viewer, a communication system, and an artificial intelligence (AI) algorithm that automatically identifies suspected LVO strokes on CTA imaging and rapidly triggers alerts. We hypothesize that the Viz application will decrease time-to-treatment, leading to improved clinical outcomes. Methods: A retrospective analysis of a prospectively maintained database was assessed for patients who presented to a stroke center currently utilizing Viz LVO and underwent EVT following transfer for LVO stroke between July 2018 and March 2020. Time intervals and clinical outcomes were compared for 55 patients divided into pre- and post-Viz cohorts. Results: The median initial door-to-neuroendovascular team (NT) notification time interval was significantly faster (25.0 min [IQR = 12.0] vs. 40.0 min [IQR = 61.0]; p = 0.01) with less variation ( p < 0.05) following Viz LVO implementation. The median initial door-to-skin puncture time interval was 25 min shorter in the post-Viz cohort, although this was not statistically significant ( p = 0.15). Conclusions: Preliminary results have shown that Viz LVO implementation is associated with earlier, more consistent NT notification times. This application can serve as an early warning system and a failsafe to ensure that no LVO is left behind.

BACKGROUND. An increase in frequency of acute ischemic strokes has been observed among patients presenting with acute neurologic symptoms during the coronavirus disease (COVID-19) pandemic. OBJECTIVE. The purpose of this study was to investigate the association between COVID-19 and stroke subtypes in patients presenting with acute neurologic symptoms. METHODS. This retrospective case-control study included patients for whom a code for stroke was activated from March 16 to April 30, 2020, at any of six New York City hospitals that are part of a single health system. Demographic data (age, sex, and race or ethnicity), COVID-19 status, stroke-related risk factors, and clinical and imaging findings pertaining to stroke were collected. Univariate and multivariate analyses were conducted to evaluate the association between COVID-19 and stroke subtypes. RESULTS. The study sample consisted of 329 patients for whom a code for stroke was activated (175 [53.2%] men, 154 [46.8%] women; mean age, 66.9 ± 14.9 [SD] years). Among the 329 patients, 35.3% (116) had acute ischemic stroke confirmed with imaging; 21.6% (71) had large vessel occlusion (LVO) stroke; and 14.6% (48) had small vessel occlusion (SVO) stroke. Among LVO strokes, the most common location was middle cerebral artery segments M1 and M2 (62.0% [44/71]). Multifocal LVOs were present in 9.9% (7/71) of LVO strokes. COVID-19 was present in 38.3% (126/329) of the patients. The 61.7% (203/329) of patients without COVID-19 formed the negative control group. Among individual stroke-related risk factors, only Hispanic ethnicity was significantly associated with COVID-19 (38.1% of patients with COVID-19 vs 20.7% of patients without COVID-19; p = 0.001). LVO was present in 31.7% of patients with COVID-19 compared with 15.3% of patients without COVID-19 (p = 0.001). SVO was present in 15.9% of patients with COVID-19 and 13.8% of patients without COVID-19 (p = 0.632). In multivariate analysis controlled for race and ethnicity, presence of COVID-19 had a significant independent association with LVO stroke (odds ratio, 2.4) compared with absence of COVID-19 (p = 0.011). CONCLUSION. COVID-19 is associated with LVO strokes but not with SVO strokes. CLINICAL IMPACT. Patients with COVID-19 presenting with acute neurologic symptoms warrant a lower threshold for suspicion of large vessel stroke, and prompt workup for large vessel stroke is recommended.

BACKGROUND AND PURPOSE: The National Institute of Neurological Disorders and Stroke common data elements initiative was created to provide a consistent method for recording and reporting observations related to neurologic diseases in clinical trials. The purpose of this study is to validate the subset of common data elements related to MR imaging evaluation of acute spinal cord injury. MATERIALS AND METHODS: Thirty-five cervical and thoracic MR imaging studies of patients with acute spinal cord injury were evaluated independently in 2 rounds by 5 expert reviewers. Intra- and interrater agreement were calculated for 17 distinct MR imaging observations related to spinal cord injury. These included ordinal, categoric, and continuous measures related to the length and location of spinal cord hemorrhage and edema as well as spinal canal and cord measurements. Level of agreement was calculated using the interclass correlation coefficient and kappa. RESULTS: The ordinal common data elements spinal cord injury elements for lesion center and rostral or caudal extent of edema or hemorrhage demonstrated agreement ranging from interclass correlation coefficient 0.68 to 0.99. Reproducibility ranged from 0.95 to 1.00. Moderate agreement was observed for absolute length of hemorrhage and edema (0.54 to 0.60) with good reproducibility (0.78 to 0.83). Agreement for the Brain and Spinal Injury Center score showed the lowest interrater agreement with an overall kappa of 0.27 (0.20, 0.34). For 7 of the 8 variables related to spinal cord injury, agreement improved between the first and second evaluation. Continuous diameter measures of the spinal cord and spinal canal using interclass correlation coefficient varied substantially (0.23 to 0.83). CONCLUSIONS: Agreement was more consistent for the ordinal measures of spinal cord injury than continuous measures. Good to excellent agreement on length and location of spinal cord hemorrhage and edema can be achieved with ordinal measures alone.

We present a case of an infundibular dilation at the origin of an accessory middle cerebral artery emanating from the distal A1 segment of the anterior cerebral artery. There was also partial vessel wall enhancement along this infundibulum. To our knowledge, this is the first case report with such findings.

Background and purpose Despite increasing demand for fluoroscopy-guided lumbar puncture (FG-LP), there is limited quantitative and epidemiological data on patients undergoing this procedure. Additionally, data are scarce on the correlation of iliac crest landmarks to the actual anatomical lumbar level (intercristal line). The aim of this study is to determine if (1) body mass index (BMI) correlates with skin to spinal canal distance (SCD) and (2) the iliac crest landmark correlates with the presumed anatomical landmark on cross-sectional imaging. Methods In this retrospective, single-center IRB-approved study, we assessed 495 patients who underwent FG-LP and had lumbar computed tomography/magnetic resonance imaging within 6 months of presentation. SCD was measured on the sagittal view at the L3-L4, L4-L5, and L5-S1 intervertebral levels. Results In our cohort of 495 adults (mean age ± standard deviation [SD], 53.2 ± 16.4 years), there was a statistically significant linear correlation between BMI and SCD at each intervertebral level. Mean ± SD (R2 ) SCD at L3-4, L4-5, and L5-S1 was 6.7 ± 1.6 cm (.5486), 7.4 ± 1.9 cm (.5894), and 7.8 ± 1.9 cm (.5968), respectively. The intercristal line aligned with L3-L4, L4-L5, and L5-S1 in 2.1%, 72.4%, and 6.2% of patients, respectively. Conclusions There was direct, positive linear correlation between BMI and SCD at clinically relevant lumbar disc levels. Furthermore, there is considerable anatomical variance in the intervertebral space that aligns with the superior aspect of the iliac crest.

During the Severe Acute Respiratory Syndrome Coronavirus 2 (COVID-19) pandemic, neuroradiology practices have experienced a paradigm shift in practice, which affected everything from staffing, workflow, work volumes, conferences, resident and fellowship education, and research. This article highlights adaptive strategies that were undertaken at the epicenter of the outbreak in New York City during the past 4-6 weeks, as experienced by 5 large neuroradiology academic departments.

Coronavirus disease 2019 was declared a global pandemic by the World Health Organization on March 11, 2020. There is a scarcity of data on coronavirus disease 2019-related brain imaging features. We present 5 cases that illustrate varying imaging presentations of acute encephalopathy in patients with coronavirus disease 2019. MR features include leukoencephalopathy, diffusion restriction that involves the GM and WM, microhemorrhages, and leptomeningitis. We believe it is important for radiologists to be familiar with the neuroradiologic imaging spectrum of acute encephalopathy in the coronavirus disease 2019 population.

BackgroundAuthors have noticed an increase in lung apex abnormalities on CT angiography (CTA) of the head and neck performed for stroke workup during the coronavirus disease 2019 (COVID-19) pandemic.ObjectiveTo evaluate the incidence of these CTA findings and their relation to COVID-19 infection.MethodsIn this retrospective multicenter institutional review board-approved study, assessment was made of CTA findings of code patients who had a stroke between March 16 and April 5, 2020 at six hospitals across New York City. Demographic data, comorbidities, COVID-19 status, and neurological findings were collected. Assessment of COVID-19 related lung findings on CTA was made blinded to COVID-19 status. Incidence rates of COVID-19 related apical findings were assessed in all code patients who had a stroke and in patients with a stroke confirmed by imaging.ResultsThe cohort consisted of a total of 118 patients with mean±SD age of 64.9±15.7 years and 57.6% (68/118) were male. Among all code patients who had a stroke, 28% (33/118) had COVID-19 related lung findings. RT-PCR was positive for COVID-19 in 93.9% (31/33) of these patients with apical CTA findings.Among patients who had a stroke confirmed by imaging, 37.5% (18/48) had COVID-19 related apical findings. RT-PCR was positive for COVID-19 in all (18/18) of these patients with apical findings.ConclusionThe incidence of COVID-19 related lung findings in stroke CTA scans was 28% in all code patients who had a stroke and 37.5% in patients with a stroke confirmed by imaging. Stroke teams should closely assess the lung apices during this COVID-19 pandemic as CTA findings may be the first indicator of COVID-19 infection.

BACKGROUND AND PURPOSE: Coronavirus disease 2019 (COVID-19) is an active worldwide pandemic with diverse complications. Stroke as a presentation has not been strongly associated with COVID-19. The authors aimed to retrospectively review a link between COVID-19 and acute stroke. MATERIALS AND METHODS: We conducted a retrospective case-control study of 41 cases and 82 control subjects matched by age, sex, and risk factors. Cases were patients who underwent stroke alert imaging with confirmed acute stroke on imaging between March 16 and April 5, 2020, at 6 hospitals across New York City. Control subjects were those who underwent stroke alertimaging during the same timeframe without imaging evidence of acute infarction. Data pertaining to diagnosis of COVID-19 infection, patient demographics, and risk factors were collected. A univariate analysis was performed to assess the covariate effect of risk factors and COVID-19 status on stroke imaging with positive findings. RESULTS: The mean age for cases and controls was 65.5 ± 15.3 years and 68.8 ± 13.2 years, respectively. Of patients with acute ischemic stroke, 46.3% had COVID-19 infection compared with 18.3% of controls (P = .001). After adjusting for age, sex, and risk factors, COVID-19 infection had a significant independent association with acute ischemic stroke compared with control subjects (OR, 3.9; 95% CI, 1.7–8.9; P = .001). CONCLUSIONS: We demonstrated that COVID-19 infection is significantly associated with imaging confirmation of acute ischemic stroke, and patients with COVID-19 should undergo more aggressive monitoring for stroke.

Background and Purpose— Estimation of infarction based on computed tomographic perfusion (CTP) has been challenging, mainly because of noise associated with CTP data. The Bayesian method is a robust probabilistic method that minimizes effects of oscillation, tracer delay, and noise during residue function estimation compared with other deconvolution methods. This study compares CTP-estimated ischemic core volume calculated by the Bayesian method and by the commonly used block-circulant singular value deconvolution technique. Methods— Patients were included if they had (1) anterior circulation ischemic stroke, (2) baseline CTP, (3) successful recanalization defined by thrombolysis in cerebral infarction ≥IIb, and (4) minimum infarction volume of >5 mL on follow-up magnetic resonance imaging (MRI). CTP data were processed with circulant singular value deconvolution and Bayesian methods. Two established CTP methods for estimation of ischemic core volume were applied: cerebral blood flow (CBF) method (relative CBF, 2 seconds) and cerebral blood volume method (145%). Final infarct volume was determined on MRI (fluid-attenuated inversion recovery images). CTP and MRI-derived ischemic core volumes were compared by univariate and Bland-Altman analysis. Results— Among 35 patients included, the mean/median (mL) difference for CTP-estimated ischemic core volume against MRI was −4/−7 for Bayesian CBF ( P =0.770), 20/12 for Bayesian cerebral blood volume ( P =0.041), 21/10 for circulant singular value deconvolution CBF ( P =0.006), and 35/18 for circulant singular value deconvolution cerebral blood volume ( P Conclusions— Despite existing variabilities between CTP postprocessing methods, Bayesian postprocessing increases accuracy and limits variability in CTP estimation of ischemic core.

Apparent increases in the size of cerebral metastases after stereotactic radiosurgery (SRS) can be caused by pseudoprogression or true disease progression, which poses a diagnostic challenge at conventional MRI. The purpose of this study was to assess whether interval change in DWI and perfusion MRI parameters can differentiate pseudoprogression from progressive disease after treatment with SRS.Patients with apparent growth of cerebral metastases after SRS treatment who underwent pre- and post-SRS DWI, dynamic susceptibility contrast (DSC)-MRI, and perfusion dynamic contrast-enhanced (DCE)-MRI were retrospectively evaluated. Final assignment of pseudoprogression or progressive disease was determined at 6-month follow-up imaging using the Response Assessment in Neuro-Oncology Brain Metastases criteria. Mean values of apparent diffusion coefficient (ADC), DCE-MRI-derived volume transfer constant (KOf 102 cerebral metastases evaluated, 32 lesions in 29 patients met our inclusion criteria. The mean duration of follow-up was 7.2 months (range, 6-14 months). Twenty-two lesions were determined as pseudoprogression, and 10 lesions were determined as progressive disease using the Response Assessment in Neuro-Oncology Brain Metastases criteria at 6-month follow-up MRI. The interval change pattern of our imaging parameters matched the expected patterns of treatment response for ADC (23/32 lesions; 72%; p = 0.055; odds ratio, 5.1), KPseudoprogression can be distinguished from disease progression in cerebral metastases treated with SRS via an interval decrease in relative CBV and K

BACKGROUND AND PURPOSE: Early and accurate identification of tumor progression in patients with low-grade gliomas is challenging. We aimed to assess the role of quantitative ADC analysis in the sequential follow-up of patients with low-grade gliomas as a potential imaging marker of tumor stability or progression. MATERIALS AND METHODS: In this retrospective study, patients with a diagnosis of low-grade glioma with at least 12 months of imaging follow-up were retrospectively reviewed. Two neuroradiologists independently reviewed sequential MR imaging in each patient to determine tumor progression using the Response Assessment in Neuro-Oncology criteria. Normalized mean ADC (ADC(mean)) and 10th percentile ADC (ADC(10)) values from FLAIR hyperintense tumor volume were calculated for each MR image and compared between patients with stable disease versus tumor progression using univariate analysis. The interval change of ADC values between sequential scans was used to differentiate stable disease from progression using the Fisher exact test. RESULTS: Twenty-eight of 69 patients who were evaluated met our inclusion criteria. Fifteen patients were classified as stable versus 13 patients as having progression based on consensus reads of MRIs and the Response Assessment in Neuro-Oncology criteria. The interval change of ADC values showed greater concordance with ultimate lesion disposition than quantitative ADC values at a single time point. The interval change in ADC(10) matched the expected pattern in 12/13 patients with tumor progression (overall diagnostic accuracy of 86%, P

BACKGROUND CONTEXT Preoperative imaging is essential in surgical planning for spinal deformity. While MRIs have reduced the need for invasive imaging in most cases, some patients, especially patients with prior hardware, still require CT myelograms, which involve injection of contrast into the thecal sac. Creating an algorithm that can generate a “predicted CT myelogram” may help reduce the risks associated with invasive imaging while providing valuable clinical information. PURPOSE Our study aims to develop an algorithm that utilizes the recent advances in computer vision, GANs in particular, to generate predicted CT myelograms from noncontrast CT images of the spine to reduce the need for unnecessary invasive imaging. STUDY DESIGN/SETTING Cross-sectional database review study. PATIENT SAMPLE Routine imaging data from 32 patients aged 18 or older from 01/01/2005 to 11/01/2020 that underwent both noncontrast CT and CT myelogram at a major academic center. OUTCOME MEASURES Qualitative assessment of predicted CT myelograms compared to actual CT myelograms on the 10-patient hold-out dataset. METHODS Using routine imaging data from 22 patients, we trained a GAN to generate predicted CT myelograms from noncontrast CTs. The GAN's effectiveness was then evaluated on a hold-out dataset of 10 additional patients. RESULTS We successfully trained a GAN using 1875 slices of noncontrast CT and CT myelogram data from 22 patients. When evaluated on data from a 10 patient hold-out dataset, the GAN was able to enhance the thecal sac on some of the patient images. CONCLUSIONS GANs can enhance presence of the thecal sac using information present in noncontrast CT images, but may require additional optimizations to generate complete contrast. Further optimizations and training with more data may allow GANs to reduce resource utilization and patient harms by decreasing the need for invasive imaging in the future. FDA DEVICE/DRUG STATUS This abstract does not discuss or include any applicable devices or drugs.

Background: Cervical spinal injury encompasses up to 1.5% of all pediatric injuries. Children, and more specifically infants, are a difficult subset of patients to obtain neurological exam in the setting of trauma, thus necessitating the use of cervical X-rays, CT scans, and MRI imaging. Case description: A healthy, 15-month-old boy had an unwitnessed fall down a flight of stairs and received a CT scan of the head and cervical spine in the emergency department due to cephalohematoma and mechanism of injury. The patient was initially diagnosed with a unilateral facet dislocation but after additional imaging and rigorous interdisciplinary discussions, the patient was correctly diagnosed with a congenitally absent left C5 pedicle. Surgical intervention was not pursued and the patient was discharged home with close follow up. Conclusion: In the acute trauma setting, congenital absent cervical pedicle can be difficult to differentiate from unilateral facet dislocation and may require the use of advanced imaging and close communication between the neurosurgery and radiology departments. Given the high morbidity and mortality involved in the repair of facet dislocation in a child, it is crucial to maintain high degree of clinical suspicion for absent spinal pedicle. In this case, the patient nearly underwent surgical intervention, but was ultimately able to be discharged home with no symptoms or deficits after correct diagnosis. Keywords: Cervical spine injury, Deformity, Congenital, Absence, Pedicle, Trauma, Pediatrics

A 61-year-old man with a history of alcoholic cirrhosis was transferred from an outside hospital for spontaneous bacterial peritonitis, septic shock, and respiratory failure after intubation. The patient was initially on sedation; however, more than 48 hours after the sedative was discontinued, his mental status remained depressed and he also developed new onset of conjugate rightward gaze deviation. On neurologic examination, the patient was unresponsive to verbal stimuli and sternal rub. He could not follow any command, including closing or opening eyes and squeezing hands. He had remarkable conjugate, forced eye deviation that could not be corrected to cross the midline using the vestibulo-ocular reflex. Corneal and gag reflexes were preserved. He blinked to visual threat less on the left side, had no clear facial asymmetry, and withdrew on his right arm and knees but had a flaccid left arm. His reflexes were brisker on the left biceps and brachioradialis, and the other deep tendon reflexes were absent. His plantar reflex was upgoing on the left side and downgoing on the right side. CT of the head had no significant findings.

BACKGROUND AND PURPOSE: Automated ASPECTS has the potential of reducing interobserver variability in the determination of early ischemic changes. We aimed to assess the performance of an automated ASPECTS software against the assessment of a neuroradiologist in a comparative analysis with concurrent CTP-based CBV ASPECTS. MATERIALS AND METHODS: Patients with anterior circulation stroke who had baseline NCCT and CTP and underwent successful mechanical thrombectomy were included. NCCT-ASPECTS was assessed by 2 neuroradiologists, and discrepancies were resolved by consensus. CTP-CBV ASPECTS was assessed by a different neuroradiologist. Automated ASPECTS was provided by Brainomix software. ASPECTS was dichotomized (ASPECTS ≥6 or 6 or ≤6 hours). RESULTS: A total of 58 patients were included. The interobserver agreement for NCCT ASPECTS was moderate (κ = 0.48) and marginally improved (κ = 0.64) for dichotomized data. Automated ASPECTS showed excellent agreement with consensus reads (κ = 0.84) and CTP-CBV ASPECTS (κ = 0.84). Intraclass correlation coefficients for ASPECTS across all 3 groups were 0.84 (95% CI, 0.76–0.90, raw scores) and 0.94 (95% CI, 0.91–0.96, dichotomized scores). Automated scores were comparable with consensus reads and CTP-CBV ASPECTS in patients when grouped on the basis of time from symptom onset (>6 or ≤6 hours). There was significant (P

Sacral fractures result from high-impact trauma or in the form of insufficiency or pathologic fractures, resulting from osteoporosis, radiation therapy, or malignancy. In the emergency setting, the escalating use of computed tomography has substantially increased diagnosis of sacral fractures, which are frequently occult on radiographs. Radiologists should be familiar with and create reports using the most current fracture classification systems, because this improves communication with the treatment team and optimizes patient care. Sacroplasty is a safe, minimally invasive treatment option for many types of sacral fractures. It provides rapid and durable pain relief, with a low incidence of complications.

Radiology has undergone two major technological transformations since its inception. First, Ultrasound, MRI and CT radically improved on X-ray for pathology detection. Next, Picture Archive and Computer Systems (PACS) dramatically improved radiologist efficiency and diagnostic accuracy. Radiology is now, again, on the precipice of another radical technological transformation—artificial intelligence (AI).

Background and Purpose Recently, the SpineJack has gained FDA clearance for marketing in the United States. These systems are quick and easy to deploy and have the advantage of being installed percutaneously under local anesthesia. As such, they are currently transforming the treatment landscape for patients with osteoporotic and malignant vertebral compression fractures (VCFs). Given the recency of this clearance, there is a dearth of information in the literature pertaining to experience with implementing the SpineJack in the United States. This study seeks to provide one of the first detailed analyses of outcomes following the use of the SpineJack for treating osteoporotic and maliganant VCFs in the United States. This study will focus on determining the extent to which the SpineJack is able to achieve adequate vertebral height restoration, pain reduction, and functional restoration, while minimizing the incidence of adjacent level fractures and volume of cement required to be injected into the vertebrae. Methods Retrospective data will be collected from cases at our institution in which the SpineJack was applied to treat patients presenting with osteoporotic or maliganant VCFs. We expect to acquire data from approximately 25 cases of SpineJack procedures used to treat VCF, representing our instituition’s collective early experiences with this novel system. A detailed dataset will be generated from each case, including patient demographics, fracture etiology and characteristics, medical comorbidities, procedure characteristics, procedure-related complications, resource utilization outcomes, pain and disability outcomes, as well as quantitative measures of radiographic endpoints obtained from follow up spine CT studies. Restoration of vertebral height, as determined by the vertebral body height ratio, is the primary endpoint. Secondary enpoints include pain reduction measured by VAS score, functional improvement measured by the Owestry Disability Index, and the rate of adjacent level fractures. Complete datasets will be collected from cases pre-operatively, as well as 1, 3, and 6 months post-operatively. Expected Outcomes We anticipate observing that the SpineJack achieves adequate restoration of vertebral height with shorter procedure times and smaller volumes of cement relative to previously reported values for other vertebral augmentation described in the literature. We also expect to observe significant and sustained improvement in both pain and function scores at pre-determined time points up to at least 6 months post-operation compared to baseline scores measured pre-operatively. Discussion With a strong mechanistic rationale based on the promising findings from a previous prospective study carried out in Europe, this study will provide among the first comprehensive characterizations of early experiences with the SpineJack in the United States. As with any early experiences with a novel technology, key insights that improve future use of the technology may be gleaned from rigorous analysis of thoroughly collected data. Disclosures M. Martini: None. K. Yaeger: None. D. Nistal: None. A. Doshi: None. R. De Leacy: None.

BACKGROUND AND PURPOSE: The Bayesian probabilistic method has shown promising results to offset noise-related variability in perfusion analysis. Using CTP, we aimed to find optimal Bayesian-estimated thresholds based on multiparametric voxel-level models to estimate the ischemic core in patients with acute ischemic stroke. MATERIALS AND METHODS: Patients with anterior circulation acute ischemic stroke who had baseline CTP and achieved successful recanalization were included. In a subset of patients, multiparametric voxel-based models were constructed between Bayesian-processed CTP maps and follow-up MRIs to identify pretreatment CTP parameters that were predictive of infarction using robust logistic regression. Subsequently CTP-estimated ischemic core volumes from our Bayesian model were compared against routine clinical practice oscillation singular value decomposition–relative cerebral blood flow

Background: Several fusion adjuncts exist to enhance fusion rates during minimally invasive transforaminal lumbar interbody fusion (MI-TLIF). The objective of this study was to compare fusion rates in patients undergoing MI-TLIF with either rhBMP-2 or cellularized bone matrix (CBM). Methods: We conducted a single surgeon retrospective cohort study of patients who underwent MI-TLIF with either rhBMP-2 or CBM placed in an interbody cage. Single and multilevel procedures were included. Fusion was assessed on computed tomography scans at 12-month follow-up by an independent, blinded, board-certified neuroradiologist. Fusion rates and rate of revision surgery were compared with a Fisher exact test between the 2 groups. A multivariate regression analysis was performed to identify patient factors that were predictive of radiographic nonunion after MI-TLIF. Results: A total of 93 fusion levels in 78 patients were reviewed. Thirty-nine patients received CBM, and 39 patients received rhBMP-2. The patients receiving rhBMP-2 were older on average (61.4 vs 55.6, P = .03). The overall fusion rate was 68% in the CBM group (32/47 levels) and 78% in the rhBMP-2 group (36/46) (P = .35). Only preoperative hypertension was predictive of radiographic nonunion (odds ratio = 3.5, P = .05). There were 3 smokers in the CBM group and 4 smokers in the BMP group, and 1 in each group experienced radiographic pseudarthrosis. A total of 4 patients, 3 in the CBM group and 1 in the BMP group (P = .61), required revision for symptomatic pseudarthrosis. All of these patients had a single-level index procedure. Conclusions: There were no differences in radiographic fusion and rate of revision surgery in patients who underwent MI-TLIF with either rhBMP-2 or CBM as fusion adjuncts. Level of Evidence: 3 Clinical Relevance: Both rhBMP-2 and CBMs can be used as effective fusion adjuncts without any clear advantage of one over the other.

Osseous metastases are the most common spine tumor and increasingly prevalent as advances in cancer treatments allow patients to live longer with their disease. Evidence-based algorithms derive the majority of their data from imaging studies and reports; the radiologist should understand the most current treatments and report in the language of the treatment team for efficient and effective communication and patient care. Advanced imaging techniques such as diffusion-weighted imaging and dynamic contrast-enhanced MRI are increasingly used for diagnosis and problem solving. Radiologists have a growing role in treatment of patients with metastatic disease, performing cement augmentation and tumor ablation.

Background Pulmonary tuberculosis (PTB) is a global health problem and remains the leading infectious cause of death worldwide. Differentiation between secondary PTB and non-tuberculous (non-TB) pneumonia is important for patient isolation and treatment, but can be difficult to determine clinically and radiologically. We proposed the application of deep learning to chest computerized tomography (CT) to assist doctors in detecting and differentiating PTB from non-TB pneumonia in an expedient, non-invasive, and reproducible manner. Methods: We retrospectively collected a dataset containing 1,124 CT scans from 923 PTB and non-TB pneumonia based on their pathological reports of lung biopsy and clinical information and 201 patients without pulmonary infiltrate from West China Hospital between 2012 and 2018. Randomly selected parts of this dataset (WCPR dataset) were used to develop, train, internally validate and test the algorithm. Patients in the WCPR dataset (PTB, n=439; non-TB pneumonia, n=484; normal, n= 201) were randomly assigned in three non-overlapping sets: training set, n=866; validation set, n=108; and test set, n=150. An additional dataset from NIH TB Portal31 comprising of cases from three countries (Belarus, n = 274; Romania, n = 43; Moldova, n = 10) was used to validate externally the algorithm's ability to identify PTB. A convolutional neural network of Inception-Res-Net-v230 was trained and tested on the entire chest CT to mimic real life application. The performance of our algorithm was compared to three trained radiology/pulmonology physicians. Findings For differentiating pulmonary infiltrates, the algorithm achieved 99·3% accuracy (149 out of 150), 99.0% sensitivity, and 100·0% specificity. For identifying PTB, the algorithm achieved 82·0% accuracy (123 out of 150), 95·9% sensitivity, and 75·2% specificity. For identifying non-TB pneumonia, the algorithm achieved 81·3% accuracy (122 out of 150), 52·7% sensitivity, and 97·9% specificity. This mostly outperformed our human readers for PTB identification, who averaged up to 81·1% accuracy, 70·8% sensitivity, and 86·1% specificity. Our algorithm identified 287 out of 327 PTB (87·8% accuracy) cases in NIH TB Portal Dataset from other countries. Interpretation: Our deep-learning-based algorithm successfully differentiated abnormal from normal chest CTs, as well as PTB from non-TB pneumonia cases and thus allows real world applicability. Early identification of PTB from non-TB pneumonia can help control outbreaks through isolation and early appropriate treatment. The application of our algorithm could expedite the identification of PTB, thereby improving clinical outcomes. Our datasets and algorithm used in this study will be publicly available to facilitate world-wide adoption. Funding Statement: The authors declare: "None." Declaration of Interests: The authors declare: "None." Ethics Approval Statement: This study was approved by the Institutional Review Board of West China Hospital (approval No. 2019-148) and Icahn School of Medicine at Mount Sinai (approval No. GCO#1: 19-0569(0001) ISMMS), and the patients’ written consents were waived.

Beyond fat suppression (FS), the efficacy of (fat-water separation or Dixon [FWD]) Dixon imaging in gadolinium-enhanced spine imaging has yet to be validated. This study evaluated enhanced opposed-phase (OP) and fat-only (FO) images along with water-only (WO; FS) images against traditional unenhanced techniques and rated the incremental value of in-phase imaging in patients with presumed neoplastic focal spine lesions.A retrospective cohort study of 36 subjects with focal spine lesions imaged with FWD was evaluated qualitatively and quantitatively.Enhanced OP, WO, and FO images were of significant value in detection of osseous lesions, surpassing the lesion conspicuity with conventional techniques both qualitatively and quantitatively, although the impact of in-phase imaging was limited. Water-only imaging performed well for FS.Contrast-enhanced FO, WO, and OP outperform traditional techniques, providing reliable lesion characterization and highest conspicuity. In-phase imaging offered limited impact on the subjective assessment of enhancement. The added value and robustness of FWD, particularly the unique contrast provided by FO imaging, suggests consideration for routine use for postgadolinium spine imaging.

Background and Purpose- Estimation of infarction based on computed tomographic perfusion (CTP) has been challenging, mainly because of noise associated with CTP data. The Bayesian method is a robust probabilistic method that minimizes effects of oscillation, tracer delay, and noise during residue function estimation compared with other deconvolution methods. This study compares CTP-estimated ischemic core volume calculated by the Bayesian method and by the commonly used block-circulant singular value deconvolution technique. Methods- Patients were included if they had (1) anterior circulation ischemic stroke, (2) baseline CTP, (3) successful recanalization defined by thrombolysis in cerebral infarction ≥IIb, and (4) minimum infarction volume of5 mL on follow-up magnetic resonance imaging (MRI). CTP data were processed with circulant singular value deconvolution and Bayesian methods. Two established CTP methods for estimation of ischemic core volume were applied: cerebral blood flow (CBF) method (relative CBF,30% within the region of delay2 seconds) and cerebral blood volume method (2 mL per 100 g within the region of relative mean transit time145%). Final infarct volume was determined on MRI (fluid-attenuated inversion recovery images). CTP and MRI-derived ischemic core volumes were compared by univariate and Bland-Altman analysis. Results- Among 35 patients included, the mean/median (mL) difference for CTP-estimated ischemic core volume against MRI was -4/-7 for Bayesian CBF ( P=0.770), 20/12 for Bayesian cerebral blood volume ( P=0.041), 21/10 for circulant singular value deconvolution CBF ( P=0.006), and 35/18 for circulant singular value deconvolution cerebral blood volume ( P0.001). Among all methods, Bayesian CBF provided the narrowest limits of agreement (-28 to 19 mL) in comparison with MRI. Conclusions- Despite existing variabilities between CTP postprocessing methods, Bayesian postprocessing increases accuracy and limits variability in CTP estimation of ischemic core.

BACKGROUND AND PURPOSE: Switching of magnetic field gradients is the primary source of acoustic noise in MR imaging. Sound pressure levels can run as high as 120 dB, capable of producing physical discomfort and at least temporary hearing loss, mandating hearing protection. New technology has made quieter techniques feasible, which range from as low as 80 dB to nearly silent. The purpose of this study was to evaluate the image quality of new commercially available quiet T2 and quiet FLAIR fast spin-echo PROPELLER acquisitions in comparison with equivalent conventional PROPELLER techniques in current day-to-day practice in imaging of the brain. MATERIALS AND METHODS: Thirty-four consecutive patients were prospectively scanned with quiet T2 and quiet T2 FLAIR PROPELLER, in addition to spatial resolution–matched conventional T2 and T2 FLAIR PROPELLER imaging sequences on a clinical 1.5T MR imaging scanner. Measurement of sound pressure levels and qualitative evaluation of relative image quality was performed. RESULTS: Quiet T2 and quiet T2 FLAIR were comparable in image quality with conventional acquisitions, with sound levels of approximately 75 dB, a reduction in average sound pressure levels of up to 28.5 dB, with no significant trade-offs aside from longer scan times. CONCLUSIONS: Quiet FSE provides equivalent image quality at comfortable sound pressure levels at the cost of slightly longer scan times. The significant reduction in potentially injurious noise is particularly important in vulnerable populations such as children, the elderly, and the debilitated. Quiet techniques should be considered in these special situations for routine use in clinical practice.

Background Fibrous dysplasia (FD) of the skull base can manifest with optic nerve compression. As most patients initially do not experience vision loss, controversy exists whether to proceed with prophylactic surgical decompression or elect for conservative observation. Optical coherence tomography (OCT), a physiologic imaging modality widely used to assess the condition of the retinal nerve fiber layer (RNFL), has been useful in monitoring compressive tumors on the optic nerve. This study evaluated potential use of OCT in management of patients with fibrous dysplasia and optic nerve involvement. Methods Six patients with suspected optic nerve compression who underwent OCT imaging as part of a neuro-ophthalmic examination were reviewed over a 2-year period. Patient records were evaluated for visual examination measures, most notably the presence of optic neuropathy, and radiographic measures on computed tomography. Measures were compared by age-adjusted RNFL thickness (above or below fifth percentile) on OCT imaging. Results Two patients were found to have mild optic neuropathy in 1 eye each. Three of 12 eyes fell below the age-adjusted fifth percentile of RNFL thickness. Presence of optic neuropathy was associated with abnormal age-adjusted RNFL thickness but not with optic nerve compression (P = 0.45). Conclusions Abnormal RNFL thickness as measured by OCT better predicted the presence of optic neuropathy than computed tomography alone. OCT may be a valuable imaging modality to monitor patients with fibrous dysplasia for development of optic neuropathy during periods of conservative watchful waiting.

BACKGROUND AND PURPOSE: Patients with acute stroke with robust collateral flow have better clinical outcomes and may benefit from endovascular treatment throughout an extended time window. Using a multiparametric approach, we aimed to identify MR perfusion parameters that can represent the extent of collaterals, approximating DSA. MATERIALS AND METHODS: Patients with anterior circulation proximal arterial occlusion who had baseline MR perfusion and DSA were evaluated. The volume of arterial tissue delay (ATD) at thresholds of 2–6 seconds (ATD 2–6 seconds ) and >6 seconds (ATD >6 seconds ) in addition to corresponding values of normalized CBV and CBF was calculated using VOI analysis. The association of MR perfusion parameters and the status of collaterals on DSA were assessed by multivariate analyses. Receiver operating characteristic analysis was performed. RESULTS: Of 108 patients reviewed, 39 met our inclusion criteria. On DSA, 22/39 (56%) patients had good collaterals. Patients with good collaterals had significantly smaller baseline and final infarct volumes, smaller volumes of severe hypoperfusion (ATD >6 seconds ), larger volumes of moderate hypoperfusion (ATD 2–6 seconds ), and higher relative CBF and relative CBV values than patients with insufficient collaterals. Combining the 2 parameters into a Perfusion Collateral Index (volume of ATD 2–6 seconds × relative CBV 2–6 seconds ) yielded the highest accuracy for predicting collateral status: At a threshold of 61.7, this index identified 15/17 (88%) patients with insufficient collaterals and 22/22 (100%) patients with good collaterals, for an overall accuracy of 94.1%. CONCLUSIONS: The Perfusion Collateral Index can predict the baseline collateral status with 94% diagnostic accuracy compared with DSA.

Radiologic imaging is often employed to supplement clinical evaluation in cases of suspected central nervous system (CNS) infection. While computed tomography (CT) is superior for evaluating osseous integrity, demineralization, and erosive changes and may be more readily available at many institutions, magnetic resonance imaging (MRI) has significantly greater sensitivity for evaluating the cerebral parenchyma, cord, and marrow for early changes that have not yet reached the threshold for CT detection. For these reasons, MRI is generally superior to CT for characterizing bacterial, viral, fungal, and parasitic infections of the CNS. The typical imaging features of common and uncommon CNS infectious processes are reviewed.

Introduction: Good collateral flow is an independent predictor of reperfusion that can be used to extend the treatment window in the new era of endovascular therapies for patients with acute ischemic stroke (AIS). Using a multiparametric approach, we aimed to identify perfusion parameter/s that can represent the extent of collaterals in comparison to CTA. Methods: AIS patients with anterior circulation large vessel occlusion who had baseline CTA and CT perfusion were included. CT perfusion data were processed by Bayesian method to generate arterial tissue delay (ATD) maps at thresholds of 2 & 6 seconds. The volume of mild delayed perfusion (Vol-ATD >2sec ), moderate delayed (Vol-ATD 2-6sec ) and critical delayed perfusion (Vol-ATD >6sec ) in addition to corresponding rCBV and rCBF were calculated. Baseline CTA collaterals were scored using an established scoring scale1 and dichotomized to poor or good. The association of perfusion parameters and status of collaterals was assessed by repeated measure of analyses and receiver operating characteristic (ROC). Results: In 28 patients included, 16 had good collaterals on CTA. After controlling for age, sex, baseline NIHSS and type of treatment, multivariate logistic regression analysis identified rCBV (p2-6sec (p=0.003), but not rCBF, Vol-ATD > 2sec or Vol-ATD >6sec , as independent predictors of good collaterals. ROC analysis showed AUC of 0.88 (sensitivity/specificity: 75%/100%) for rCBV and AUC of 0.84 (sensitivity/specificity: 93%/67%) for Vol-ATD 2-6sec . We defined a perfusion collateral index (PCI) calculated from Vol-ATD 2-6sec x its rCBV, that remained an independent predictor of good collaterals with improved diagnostic accuracy over each measure alone resulting in nominal AUC of 1 (sensitivity/specificity: 100%/100%). Conclusions: Multiparametric CT perfusion can be used to assess the status of collaterals in patients with AIS. Perfusion collateral index (PCI) defined as Vol-ATD 2-6sec x rCBV is a new perfusion index with a nominal diagnostic accuracy of 100% compared to baseline CTA to predict status of collaterals in our small cohort. Our results need to be validated in a larger prospective cohort.

1. To learn the pertinent radiologic anatomy, including bony, neural, and vascular anatomy, as it relates to image-guided lumbar spine biopsy 2. To review the most common indications and contraindications for image-guided lumbar spine biopsy 3. To review different approaches and techniques when planning image-guided coaxial lumbar spine biopsy

BACKGROUND AND PURPOSE: CT-guided biopsy is the most commonly used method to obtain tissue for diagnosis in suspected cases of malignancy involving the spine. The purpose of this study was to demonstrate that a low-dose CT-guided spine biopsy protocol is as effective in tissue sampling as a regular-dose protocol, without adversely affecting procedural time or complication rates. MATERIALS AND METHODS: We retrospectively reviewed all patients who underwent CT-guided spine procedures at our institution between May 2010 and October 2013. Biopsy duration, total number of scans, total volume CT dose index, total dose-length product, and diagnostic tissue yield of low-dose and regular-dose groups were compared. RESULTS: Sixty-four patients were included, of whom 31 underwent low-dose and 33 regular-dose spine biopsies. There was a statistically significant difference in total volume CT dose index and total dose-length product between the low-dose and regular-dose groups (P < .0001). There was no significant difference in the total number of scans obtained (P = .3385), duration of procedure (P = .149), or diagnostic tissue yield (P = .6017). CONCLUSIONS: Use of a low-dose CT-guided spine biopsy protocol is a practical alternative to regular-dose approaches, maintaining overall quality and efficiency at reduced ionizing radiation dose.

The Raymond-Roy Occlusion Classification (RROC) is the standard for evaluating coiled aneurysms (Class I: complete obliteration; Class II: residual neck; Class III: residual aneurysm), but not all Class III aneurysms behave the same over time.This is a retrospective review of 370 patients with 390 intracranial aneurysms treated with coil embolization. A Modified Raymond-Roy Classification (MRRC), in which Class IIIa designates contrast within the coil interstices and Class IIIb contrast along the aneurysm wall, was applied retrospectively.Class IIIa aneurysms were more likely to improve to Class I or II than Class IIIb aneurysms (83.34% vs 14.89%, p0.001) and were also more likely than Class II to improve to Class I (52.78% vs 16.90%, p0.001). Class IIIb aneurysms were more likely to remain incompletely occluded than Class IIIa aneurysms (85.11% vs 16.67%, p0.001). Class IIIb aneurysms were larger with wider necks while Class IIIa aneurysms had higher packing density. Class IIIb aneurysms had a higher retreatment rate (33.87% vs 6.54%, p0.001) and a trend toward higher subsequent rupture rate (3.23% vs 0.00%, p=0.068).We propose the MRRC to further differentiate Class III aneurysms into those likely to progress to complete occlusion and those likely to remain incompletely occluded or to worsen. The MRRC has the potential to expand the definition of adequate coil embolization, possibly decrease procedural risk, and help endovascular neurosurgeons predict which patients need closer angiographic follow-up. These findings need to be validated in a prospective study with independent blinded angiographic grading.