BACKGROUND AND PURPOSE:Epidural spinal cord compression (ESCC) is an important cause of disability among patients with cancer. Early detection is crucial for optimizing clinical outcomes. MRI is the preferred imaging technique for ruling out ESCC and is frequently requested in radiology departments, particularly in the emergent setting. However, data on the efficacy and diagnostic yield of total spine MRI for the diagnosis of ESCC in oncology patients remain limited. This study evaluates the frequency of positive findings and associated risk factors in a tertiary cancer center. MATERIALS AND METHODS:This retrospective study included patients who underwent total spine MRI for the assessment of ESCC during a 3-year period. A standardized noncontrast MRI protocol was used. Clinical and imaging data, including patient demographics (sex, age); tumor pathology; tumor, node, metastasis stage; ESCC grade; symptoms; prior treatments (radiation therapy, surgery, chemotherapy); and ordering physician/department, were retrospectively reviewed. Patients were categorized into 2 groups on the basis of the presence or absence of cord compression (ESCC 2 or 3). Associations between ESCC and other variables were assessed via the Wilcoxon rank-sum test, Pearson χ2 test, and Fisher exact test. Statistical significance was defined as P < .05. RESULTS:Among 289 patients (median age, 66 years; 148 women) and 300 total spine MRI examinations, ESCC was detected in 18 cases (6.0%). Significant associations with ESCC included advanced tumor, node, metastasis stage (P = .028) and prior treatments, such as radiation to the site of compression (P = .002), decompression surgery (P = .011), and recent systemic chemotherapy (P < .001). Bone metastases to the spine on body CT examinations performed within 2 weeks before MRI also correlated with ESCC (P < .001). Notably, no ESCC cases occurred in patients without spine bone metastases on recent body CT or in those with less than stage IV disease. Patient symptoms did not correlate with ESCC presence (P = .3). CONCLUSIONS:This study suggests that the diagnostic yield of total spine MRI for ESCC in oncology patients is relatively low and may be improved by refining the selection criteria. Patients with advanced-stage disease, prior spinal interventions, and bone metastases on recent body CT may be at higher risk.

This study aims to assess the effectiveness of integrating Segment Anything Model (SAM) and its variant MedSAM into the automated mining, object detection, and segmentation (MODS) methodology for developing robust lung cancer detection and segmentation models without post hoc labeling of training images. In a retrospective analysis, 10,000 chest computed tomography scans from patients with lung cancer were mined. Line measurement annotations were converted to bounding boxes, excluding boxes < 1 cm or > 7 cm. The You Only Look Once object detection architecture was used for teacher-student learning to label unannotated lesions on the training images. Subsequently, a final tumor detection model was trained and employed with SAM and MedSAM for tumor segmentation. Model performance was assessed on a manually annotated test dataset, with additional evaluations conducted on an external lung cancer dataset before and after detection model fine-tuning. Bootstrap resampling was used to calculate 95% confidence intervals. Data mining yielded 10,789 line annotations, resulting in 5403 training boxes. The baseline detection model achieved an internal F1 score of 0.847, improving to 0.860 after self-labeling. Tumor segmentation using the final detection model attained internal Dice similarity coefficients (DSCs) of 0.842 (SAM) and 0.822 (MedSAM). After fine-tuning, external validation showed an F1 of 0.832 and DSCs of 0.802 (SAM) and 0.804 (MedSAM). Integrating foundational segmentation models into the MODS framework results in high-performing lung cancer detection and segmentation models using only mined clinical data. Both SAM and MedSAM hold promise as foundational segmentation models for radiology images.

Virtual reality (VR) and augmented Reality (AR) are emerging technologies with the potential to revolutionize Interventional radiology (IR). These innovations offer advantages in patient care, interventional planning, and educational training by improving the visualization and navigation of medical images. Despite progress, several challenges hinder their widespread adoption, including limitations in navigation systems, cost, clinical acceptance, and technical constraints of AR/VR equipment. However, ongoing research holds promise with recent advancements such as shape-sensing needles and improved organ deformation modeling. The development of deep learning techniques, particularly for medical imaging segmentation, presents a promising avenue to address existing accuracy and precision issues. Future applications of AR/VR in IR include simulation-based training, preprocedural planning, intraprocedural guidance, and increased patient engagement. As these technologies advance, they are expected to facilitate telemedicine, enhance operational efficiency, and improve patient outcomes, marking a new frontier in interventional radiology.

Abstract Patients with a small posterior cranial fossa may present with cerebellar tonsillar herniation through the foramen magnum, known as Chiari malformation (CM). The relationship between CM, pituitary volume (PV), and growth hormone deficiency (GHD) has not yet been explored and is the subject of this abstract. This study seeks to compare the differences in PV in short patients with CM with a diagnosis of either GHD or idiopathic short stature (ISS), to normal controls (NCs). The database of a Peds Endo Center between 2013-21 was queried for patients with CM and who had undergone MRI evaluation. Patients were separated into 4 groups: CM and GHD, CM and ISS, GHD without CM, and ISS without CM. These groups’ PV results were compared with NCs who we previously reported. The ages of short patients with CM (n=29) were compared to the ages of NCs (n=170); no significant difference was found (p = 0.12). The MN and MD PV for patients with GHD alone were 230.8 ± 89.64 and 217.62mm3, respectively. The MN and MD PV for patients with GHD and CM (n=23) were 246.55 ± 128.0 and 200.5mm3, respectively. The MN and MD PV for CM and ISS (n=6) were 671.54 ± 350.25 and 619.55mm3, respectively. The MN and MD PV for NCs were 364.0 ± 145.2 and 346.0mm3, respectively. The PV of patients with GHD alone were compared to the PV of patients with both GHD and CM; there was no significant difference found (p=1.0). Next, the PV of patients with GHD alone were compared to the PV of patients with both ISS and CM which showed that patients with GHD alone had significantly smaller PV compared to patients with both ISS and CM (p<0.05). Lastly, we compared the PV of patients with both GHD and CM versus patients with both ISS and CM, which showed that patients with both GHD and CM had significantly smaller PVs compared to patients with both ISS and CM (p<0.05). The PV of short patients with CM (n=29) were compared to the PV of NCs (n=170) and there was no significant difference found (p = 0.58). Our study demonstrates that PV is smaller in patients with GHD regardless of whether they have CM or not. We speculate that CM appears to be a radiological finding with no significant impact on PV, whereas GHD appears to have a significant impact on PV. Therefore we speculate the small PV exhibited in patients with CM and GHD appear to be related to GHD. A larger sample size will be needed to further elaborate on this concept. Presentation: Monday, June 13, 2022 12:30 p.m. - 2:30 p.m.

BACKGROUND:Numerous case reports and case series have described brain Magnetic Resonance Imaging (MRI) findings in Coronavirus disease 2019 (COVID-19) patients with concurrent posterior reversible encephalopathy syndrome (PRES). PURPOSE:We aim to compile and analyze brain MRI findings in patients with COVID-19 disease and PRES. METHODS:PubMed and Embase were searched on April 5th, 2021 using the terms "COVID-19", "PRES", "SARS-CoV-2" for peer-reviewed publications describing brain MRI findings in patients 21 years of age or older with evidence of severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) infection and PRES. RESULTS:Twenty manuscripts were included in the analysis, which included descriptions of 30 patients. The average age was 57 years old. Twenty-four patients (80%) required mechanical ventilation. On brain MRI examinations, 15 (50%) and 7 (23%) of patients exhibited superimposed foci of hemorrhage and restricted diffusion respectively. CONCLUSIONS:PRES is a potential neurological complication of COVID-19 related disease. COVID-19 patients with PRES may exhibit similar to mildly greater rates of superimposed hemorrhage compared to non-COVID-19 PRES patients.

Abstract Background MRIs of the brain in patients with short stature have shown a number of abnormalities. Some of these radiological findings can have clinical significance. Here we have looked at MRI results in such a population. Objective To review the value and significance of the prevalence of all abnormal MRI findings of children with short stature who are to undergo growth hormone therapy (GHT). Materials and methods This study involved a retrospective review of MRI findings in all children prescribed GHT within a pediatric health network's database from Jan 2020 to Aug 2021. Post-gadolinium contrast enhanced brain and pituitary MRIs utilizing 2 mm slices were used to calculate pituitary volume. Pituitary volume was calculated using the ellipsoid formula (LxWxH/2). Pediatric patients diagnosed with non-acquired GHD or ISS, with MRIs having been performed between Jan 2020 and Aug 2021 and having been prescribed GHT by Aug 2021 were included in this study. Patients who experienced other endocrine abnormalities such as SGA, Turner Syndrome, and Noonan Syndrome were excluded. Patients with obstruction of sellar and parasellar religion due to movement artifacts or magnetic interference on their MRIs were also excluded. Results Of one hundred and twelve patients found, eighty one met criteria for inclusion in this study. Of the eighty one MRIs reviewed, twenty eight children, 34.6%, had normal pituitary anatomy and fifty three, 65.4%, had a pituitary abnormality. Out of the fifty three with a pituitary abnormality, forty three subjects, 81.1%, were determined to have a small pituitary volume, including significant pituitary hypoplasia. Ten subjects (18.9%) had an enlarged pituitary volume (pituitary hyperplasia). Of these ten patients who had an enlarged pituitary volume, eight were pubertal (80%). Nine children with a pituitary abnormality (16.9%) had additional structural anomalies on their MRIs. One had a small left frontal developmental venous anomaly. Two had Rathke's cleft cysts. Two had pars intermedia cysts. One had a small right parietal developmental venous anomaly. One had a small left parietal developmental venous anomaly. One had a left cerebellar tonsillar ectopia bordering on chiari malformation (.5 mm away on the coronal plane). One had a small lobulation (semi-bulbous projection) of the anterior pituitary gland, superior and anterior to the infundibular stalk. Conclusion Prevalence of brain abnormalities in children with short stature who are to undergo GHT is significant and warrants MRI evaluations in these subjects. Presentation: Saturday, June 11, 2022 1:00 p.m. - 3:00 p.m., Monday, June 13, 2022 12:58 p.m. - 1:03 p.m.

Abstract Background Pituitary cysts (PCs) may be related to the development of diminished growth hormone secretion because they may limit the proliferation of somatotrophs. This study seeks to investigate the mass effect of PCs on the pituitary function. Methods Patients aged 6-18 with cysts and follow-ups between 2007–21 were compared to normal controls (NCs) aged 6-18 from a neuroradiology center. Pituitary volume (PV) is the volume of the pituitary gland including the cyst, while net pituitary volume (netPV) is the volume of the pituitary gland excluding the cyst. Since NCs did not have PCs, only PV was utilized. PVs and netPVs are reported in mm3. Data were stratified into prepubertal (age < 11 yrs) and pubertal (age > 11 yrs). The Kruskal-Wallis One Way ANOVA on Ranks was utilized to compare multiple means, and the Kruskal-Wallis Multiple-Comparison Z Value test (with Bonferroni adjustment) was utilized for pairwise comparisons. Results The mean and median PVs of prepubertal GHD (n=37), ISS (n=5), and NCs (n=58) were 290.2 ± 109.7 and 305.0, 314.4 ± 100.8 and 299.8, and 246.8 ± 63.7 and 241.6, respectively. The difference between mean PVs of prepubertal GHD, ISS, and NCs was not significant. The mean and median PVs of pubertal GHD (n=58), ISS (n=33), and NCs (n=112) were 391.5 ± 163.5 and 370.2, 409.2 ± 215.8 and 382.9, and 424.2 ± 138.9 and 402.7, respectively. The difference between mean PVs of pubertal GHD, ISS, and NCs was not significant. For netPV, the mean and median values for prepubertal GHD and ISS patients were 252.2 ± 83.3 and 272.2, and 245.2 ± 85.7 and 244.9, respectively. The difference between mean netPVs of prepubertal GHD, ISS, and NCs was not significant. For netPV, the mean and median values for pubertal GHD and ISS patients were 332.7 ± 121.3 and 346.4, and 333.9 ± 146.1 and 330.7, respectively. The mean netPVs of pubertal GHD and ISS patients were both significantly lower than the mean PV of pubertal NCs. The mean and median PVs for cyst patients were 364.8 ± 170.0 and 347.8 which was not significantly different from the NCs. The mean and median netPVs for cyst patients were 307.3 ± 122.9 and 289.0 which was significantly different from the NCs (p<0.001). Conclusion When considering the functional component of the pituitary gland, cyst volume should be subtracted from the overall pituitary gland. Presentation: Sunday, June 12, 2022 12:36 p.m. - 12:41 p.m., Monday, June 13, 2022 12:30 p.m. - 2:30 p.m.

Abstract Objectives We have previously shown that pituitary cysts may affect growth hormone secretion. This study sought to determine cyst evolution during growth hormone treatment in children. Methods Forty-nine patients with short stature, a pituitary cyst, and at least two brain MRI scans were included. The percent of the pituitary gland occupied by the cyst (POGO) was calculated, and a cyst with a POGO of ≤15% was considered small, while a POGO >15% was considered large. Results Thirty-five cysts were small, and 14 were large. Five of the 35 small cysts grew into large cysts, while 6 of the 14 large cysts shrunk into small cysts. Of 4 cysts that fluctuated between large and small, 3 presented as large and 1 as small. Small cysts experienced greater change in cyst volume (CV) (mean=61.5%) than large cysts (mean=−0.4%). However, large cysts had a greater net change in CV (mean=44.2 mm3) than small cysts (mean=21.0 mm3). Older patients had significantly larger mean pituitary volume than younger patients (435.4 mm3 vs. 317.9 mm3) and significantly larger mean CV than younger patients (77.4 mm3 vs. 45.2 mm3), but there was no significant difference in POGO between groups. Conclusions Pituitary cyst size can vary greatly over time. Determination of POGO over time is a useful marker for determining the possibility of a pathologic effect on pituitary function since it factors both cyst and gland volume. Large cysts should be monitored closely, given their extreme, erratic behavior.

4D-parathyroid CT scans have become a mainstay in the evaluation and pre-surgical planning for parathyroid adenomas. Most protocols typically rely on non-contrast images, prior to the arterial and delayed phases. Previous reports with dual-energy CT imaging have highlighted the utility of virtual non-contrast images to help reduce radiation dose while maintaining diagnostic accuracy. Herein, we report two cases of surgically proven parathyroid adenomas diagnosed with 4D-parathyroid CT scans performed on dual-layer spectral scanners, and in retrospect highlight the utility of virtual non-contrast images. To our knowledge, this report provides the first description of virtual non-contrast images from dual-layer spectral CT scanners that could aid in the diagnosis of parathyroid adenomas, confirming similar findings described with dual-energy CT scanners.

We have shown that short children have significantly reduced pituitary volume (PV)s and have speculated PV as a cause for diminished chronic growth hormone (GH) secretion and poor growth. In this study, we further elucidate the role of PV in the etiology of short stature (SS) in a larger cohort of siblings (SBs).The database of a Peds Endo Center between 2013-21 was queried for siblings with SS who underwent a GH Stimulation test (GHST) and MRI evaluation. Their results were compared with normal controls (NCs) as previously reported. 129 SBs of 60 families were compared to 170 NCs. SBs were divided into 3 groups (GPs). GP1 (n=79) consisted of families with only GHD. GP2 (n=12) contained families with only ISS SBs. GP3 (n=38) comprised families with mixed GHD and ISS. SBs <11 yrs and >11 yrs were considered prepubertal (prePB) and pubertal (PB), RSP. The mean (MN) and median (MD) age for both prePB and PB SBs were significantly different (p 0.05). The 32 PB patients in GP3 had a mean PV of 316.17± 197.53 mm3, which was significantly different from that of the PB NCs of 424.6 ± 138.4 mm3 (p<0.001). Out of 38 children in GP3, 18 passed the GHST and 11 of those children who passed demonstrated a small pituitary gland (61%). 78% of prePB SBs had small PVs, while 88% were GHD. 66% of PB SBs had small PVs, while 70% of PB SBs were GHD. 71% of all SBs had small PVs, while 77% were GHD. When combined, GHST and PV identify the etiology for SS in 92% of subjects. The GHST and PV together identify more patients of SS who should qualify and benefit from GH therapy than the GHST alone. Since ages were significantly different and present as a limitation to this study, future studies should strive for age match control Presentation: Saturday, June 11, 2022 1:00 p.m. - 3:00 p.m.

Abstract Background Patients with diminished growth hormone (GH) secretion are candidates for GH therapy (GHT). The GH stimulation test (GHST) is considered the gold standard for the diagnosis of GH deficiency (GHD), yet its efficacy has been questioned. In this study we explore the GHST and PV's ability to define GHD and determine their individual ability to predict GHT outcomes. Subjects and Methods A database at a Pediatric Endocrinology center was queried for patients aged 6-18 yrs who underwent a GHST, MRI, and GHT between 1/2018 - 1/2021. Patients with a first follow up (FU) between 3 and 9 months were included; of these patients, second FUs were included if they occurred between 9 and 15 months. Patients with relevant comorbidities, those with GHST peak ≥ 10.0 ng/mL, and nonadherent patients were excluded. MRIs were acquired on a Philips 1.5 or 3.0 T scanner (2mm slices) and PV was calculated using the ellipsoid formula (LxWxH/2). PV and height were converted to SDS. Response to treatment was defined as change in height SDS over the assessed time interval. A multiple linear regression was utilized to analyze the response to GHT relative to peak GH and PV, with initial height and age at stimulation included as covariates. The relationship between peak GH and PV SDS was analyzed with a Pearson correlation Results The first FU ranged between 3.1 and 8.9 months, and the second FU ranged between 9.0 and 14.9 months. 145 patients had one FU, and 83 patients had two FUs. Peak GH and PV SDS were not correlated (r=0.03). Patients who were relatively shorter for their age and gender at stimulation had higher growth rates in the first interval, but not in the second interval. Both PV and peak GH provided information about response to GHT. PV SDS negatively predicted the relative growth response to treatment in the first interval (slope=-0.03, p=0.048). However, PV only explained 3.7% of variation in growth. PV SDS was not a useful predictor of response in the second interval (slope=-0.01, p=0.693). Peak GH was a predictor of response to GHT in the first interval only after accounting for age at stimulation and initial height (slope=-0.01, p=0.032; r2=0.01). Peak GH was a predictor of response in the second interval (slope=-0.02, p=0.040), explaining 5.1% of the variation in growth. Conclusion Since peak GH and PV were not correlated, they likely reflect different physiological processes. PV and peak GH both provide information about response to GHT, so they should both be utilized to determine eligibility for GHT. Presentation: Saturday, June 11, 2022 1:00 p.m. - 3:00 p.m.

Abstract Background Pituitary cysts may be implicated in short stature and affect growth hormone secretion. The natural history of cysts is not known in patients with GHD and ISS. Objective To characterize the progression of cyst volume (CV) and percentage of the gland occupied by the cyst (POGO) over time in GHD and ISS patients. Subjects and Methods A pediatric health system's database was queried for patients diagnosed with short stature and a cyst with at least one follow up MRI between 2007-21. Data up to 7 years after first follow up was included in this study. The mean and median follow up time were 1.32±1.24 and 1.00. Cysts with a POGO≤15% were considered small, while a POGO>15% were considered large. Results The mean and median %ΔCV for all patients for all their follow up MRIs were 38.27%±179.14 and 0%. The mean and median %ΔPOGO for all patients were 38.32%±219.85 and -5.79%. The mean and median %ΔCV for patients with a small cyst (SC) (n=34) were 61.49%±215.60 and 0%. The mean and median %ΔPOGO for patients with a SC were 61.62%±267.25 and -2.89%. The mean and median %ΔCV for patients with a large cyst(LC)(n=14) were -0.4% ±-79.25 and 0%. The mean and median %ΔPOGO for patients with a LC were -1.08%±90.50 and -15.67%. 5 of the 35(14.3%) SCs grew into LCs and stayed large while 6 of the 14 LCs shrunk into SCs. 4 cysts fluctuated between large and small: 3 started large and 1 started small. CV of patients with LCs has a significant negative correlation with time (-0.37, p=0.01). The slope of the regression line is -0.01 mm3/month. The CV of patients with SCs does not show any change in time (-0.02, p=0.84). There is no significant difference in POGO (p=0.86) or in CV (p=0.96) in GHD and ISS patients. In GHD and ISS patients, the difference in POGO is different in each group at each MRI date (p=0.02), but not in CV (p=0.38). GHD patients had an average ΔPOGO of -1.05, while ISS patients had an average ΔPOGO of 1.26. Conclusion POGO can change greatly over time. LCs tend to take up less of the gland over time. SCs tend not to change significantly over time, but a minority can still enlarge and need to be monitored. So far, there have been no significant clinical consequences related to these cysts. Presentation: Monday, June 13, 2022 12:30 p.m. - 2:30 p.m.

We read with great interest the recent article by Copelan et al titled, “Recent Administration of Iodinated Contrast Renders Core Infarct Estimation Inaccurate Using RAPID Software.” In a cohort of patients with acute stroke who received recent intravenous iodinated contrast as part of another imaging study, the authors demonstrated that the rapid processing of perfusion and diffusion (RAPID; iSchemaView) CTP platform may underestimate the core infarct size. This article importantly highlights inherent challenges present in interpreting scans for patients with acute stroke transferred from outside facilities who underwent recent CT imaging with iodinated contrast. We experienced a different challenge while interpreting scans for transferred patients with stroke who also received recent iodinated contrast at the outside facility. We observed parenchymal hyperdensities, likely related to contrast enhancement of acute infarcts. These parenchymal hyperdensities limited our ability to confidently exclude intracranial hemorrhage, and we described using dual-layer spectral imaging to address this problem. Nevertheless, these challenges collectively bring to light the phenomenon of recent intravenous contrast administration hindering interpretation of acute stroke examinations after a patient’s arrival to a tertiary care center for potential mechanical thrombectomy. Despite this, sparse literature exists to investigate these issues. As the authors have shown that recent contrast administration may underestimate the core infarct size with the RAPID software, we postulate that a similar phenomenon may result in overestimation of the calculated ASPECTS. Evaluation for intracranial hemorrhage, ASPECTS decay, and perfusion abnormalities is paramount for appropriate patient selection for mechanical thrombectomy after interfacility transfer. Administration of contrast material at the first facility may limit this ability at the recipient facility. We thank the authors for their important work, and we feel that additional studies are essential to address these issues.

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

To listen to the podcast associated with this article, please select one of the following: iTunes, Google Play, or direct download.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.

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.

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.

The spine and spinal cord are composed of multiple segments initiated by different embryologic mechanisms and advanced under different systems of control. In humans, the upper central nervous system is formed by primary neurulation, the lower by secondary neurulation, and the intervening segment by junctional neurulation. This article focuses on the distal spine and spinal cord to address their embryogenesis and the molecular derangements that lead to some distal spinal malformations.

OBJECTIVEPredicting vision recovery following surgical decompression of the optic chiasm in pituitary adenoma patients remains a clinical challenge, as there is significant variability in postoperative visual function that remains unreliably explained by current prognostic factors. Available literature inadequately characterizes alterations in adenoma patients involving the lateral geniculate nucleus (LGN). This study examined the association of LGN degeneration with chiasmatic compression as well as with the retinal nerve fiber layer (RNFL), pattern standard deviation (PSD), mean deviation (MD), and postoperative vision recovery. PSD is the degree of difference between the measured visual field pattern and the normal pattern ("hill") of vision, and MD is the average of the difference from the age-adjusted normal value.METHODSA prospective study of 27 pituitary adenoma patients and 27 matched healthy controls was conducted. Participants were scanned on a 7T ultra-high field MRI scanner, and 3 independent readers measured the LGN at its maximum cross-sectional area on coronal T1-weighted MPRAGE imaging. Readers were blinded to diagnosis and to each other's measurements. Neuro-ophthalmological data, including RNFL thickness, MD, and PSD, were acquired for 12 patients, and postoperative visual function data were collected on patients who underwent surgical chiasmal decompression. LGN areas were compared using two-tailed t-tests.RESULTSThe average LGN cross-sectional area of adenoma patients was significantly smaller than that of controls (13.8 vs 19.2 mm2, p < 0.0001). The average LGN cross-sectional area correlated with MD (r = 0.67, p = 0.04), PSD (r = -0.62, p = 0.02), and RNFL thickness (r = 0.75, p = 0.02). The LGN cross-sectional area in adenoma patients with chiasm compression was 26.6% smaller than in patients without compression (p = 0.009). The average tumor volume was 7902.7 mm3. Patients with preoperative vision impairment showed 29.4% smaller LGN cross-sectional areas than patients without deficits (p = 0.003). Patients who experienced improved postoperative vision had LGN cross-sectional areas that were 40.8% larger than those of patients without postoperative improvement (p = 0.007).CONCLUSIONSThe authors demonstrate novel in vivo evidence of LGN volume loss in pituitary adenoma patients and correlate imaging results with neuro-ophthalmology findings and postoperative vision recovery. Morphometric changes to the LGN may reflect anterograde transsynaptic degeneration. These findings indicate that LGN degeneration may be a marker of optic apparatus injury from chiasm compression, and measurement of LGN volume loss may be useful in predicting vision recovery following adenoma resection.

Background: Differentiating glioblastoma, brain metastasis, and central nervous system lymphoma (CNSL) on conventional magnetic resonance imaging (MRI) can present a diagnostic dilemma due to the potential for overlapping imaging features. We investigate whether machine learning evaluation of multimodal MRI can reliably differentiate these entities. Methods: Preoperative brain MRI including diffusion weighted imaging (DWI), dynamic contrast enhanced (DCE), and dynamic susceptibility contrast (DSC) perfusion in patients with glioblastoma, lymphoma, or metastasis were retrospectively reviewed. Perfusion maps (rCBV, rCBF), permeability maps (K-trans, Kep, Vp, Ve), ADC, T1C+ and T2/FLAIR images were coregistered and two separate volumes of interest (VOIs) were obtained from the enhancing tumor and non-enhancing T2 hyperintense (NET2) regions. The tumor volumes obtained from these VOIs were utilized for supervised training of support vector classifier (SVC) and multilayer perceptron (MLP) models. Validation of the trained models was performed on unlabeled cases using the leave-one-subject-out method. Head-to-head and multiclass models were created. Accuracies of the multiclass models were compared against two human interpreters reviewing conventional and diffusion-weighted MR images. Results: Twenty-six patients enrolled with histopathologically-proven glioblastoma (n=9), metastasis (n=9), and CNS lymphoma (n=8) were included. The trained multiclass ML models discriminated the three pathologic classes with a maximum accuracy of 69.2% accuracy (18 out of 26; kappa 0.540, P=0.01) using an MLP trained with the VpNET2 tumor volumes. Human readers achieved 65.4% (17 out of 26) and 80.8% (21 out of 26) accuracies, respectively. Using the MLP VpNET2 model as a computer-aided diagnosis (CADx) for cases in which the human reviewers disagreed with each other on the diagnosis resulted in correct diagnoses in 5 (19.2%) additional cases. Conclusions: Our trained multiclass MLP using VpNET2 can differentiate glioblastoma, brain metastasis, and CNS lymphoma with modest diagnostic accuracy and provides approximately 19% increase in diagnostic yield when added to routine human interpretation.