Automated assessment of ischemic core on non-contrast computed tomography: a multicenter comparative analysis with CT perfusion.

BACKGROUND: Application of machine learning (ML) algorithms has shown promising results in estimating ischemic core volumes using non-contrast CT (NCCT). OBJECTIVE: To assess the performance of the e-Stroke Suite software (Brainomix) in assessing ischemic core volumes on NCCT compared with CT perfusion (CTP) in patients with acute ischemic stroke. METHODS: In this retrospective multicenter study, patients with anterior circulation large vessel occlusions who underwent pretreatment NCCT and CTP, successful reperfusion (modified Thrombolysis in Cerbral Infarction ≥2b), and post-treatment MRI, were included from three stroke centers. Automated calculation of ischemic core volumes was obtained on NCCT scans using ML algorithm deployed by e-Stroke Suite and from CTP using Olea software (Olea Medical). Comparative analysis was performed between estimated core volumes on NCCT and CTP and against MRI calculated final infarct volume (FIV). RESULTS: A total of 111 patients were included. Estimated ischemic core volumes (mean±SD, mL) were 20.4±19.0 on NCCT and 19.9±18.6 on CTP, not significantly different (P=0.82). There was moderate (r=0.40) and significant (P<0.001) correlation between estimated core on NCCT and CTP. The mean difference between FIV and estimated core volume on NCCT and CTP was 29.9±34.6 mL and 29.6±35.0 mL, respectively (P=0.94). Correlations between FIV and estimated core volume were similar for NCCT (r=0.30, P=0.001) and CTP (r=0.36, P<0.001). CONCLUSIONS: Results show that ML-based estimated ischemic core volumes on NCCT are comparable to those obtained from concurrent CTP in magnitude and in degree of correlation with MR-assessed FIV.

Diffusion Weighted Imaging in Spine Tumors.

Diffusion weighted imaging (DWI) has developed into a powerful tool for the evaluation of spine tumors, particularly for the assessment of vertebral marrow lesions and intramedullary tumors. Advances in magnetic resonance techniques have improved the quality of spine DWI and diffusion tensor imaging (DTI) in recent years, with increased reproducibility and utilization. DTI, with quantitative parameters such as fractional anisotropy and qualitative visual assessment of nerve fiber tracts, can play a valuable role in the evaluation and surgical planning of spinal cord tumors. These widely available techniques can be used to enhance the diagnostic evaluation of spinal tumors.

AI software detection of large vessel occlusion stroke on CT angiography: a real-world prospective diagnostic test accuracy study.

BACKGROUND: Artificial intelligence (AI) software is increasingly applied in stroke diagnostics. However, the actual performance of AI tools for identifying large vessel occlusion (LVO) stroke in real time in a real-world setting has not been fully studied. OBJECTIVE: To determine the accuracy of AI software in a real-world, three-tiered multihospital stroke network. METHODS: All consecutive head and neck CT angiography (CTA) scans performed during stroke codes and run through an AI software engine (Viz LVO) between May 2019 and October 2020 were prospectively collected. CTA readings by radiologists served as the clinical reference standard test and Viz LVO output served as the index test. Accuracy metrics were calculated. RESULTS: Of a total of 1822 CTAs performed, 190 occlusions were identified; 142 of which were internal carotid artery terminus (ICA-T), middle cerebral artery M1, or M2 locations. Accuracy metrics were analyzed for two different groups: ICA-T and M1 ±M2. For the ICA-T/M1 versus the ICA-T/M1/M2 group, sensitivity was 93.8% vs 74.6%, specificity was 91.1% vs 91.1%, negative predictive value was 99.7% vs 97.6%, accuracy was 91.2% vs 89.8%, and area under the curve was 0.95 vs 0.86, respectively. Detection rates for ICA-T, M1, and M2 occlusions were 100%, 93%, and 49%, respectively. As expected, the algorithm offered better detection rates for proximal occlusions than for mid/distal M2 occlusions (58% vs 28%, p=0.03). CONCLUSIONS: These accuracy metrics support Viz LVO as a useful adjunct tool in stroke diagnostics. Fast and accurate diagnosis with high negative predictive value mitigates missing potentially salvageable patients.

RadImageNet: An Open Radiologic Deep Learning Research Dataset for Effective Transfer Learning.

Purpose: To demonstrate the value of pretraining with millions of radiologic images compared with ImageNet photographic images on downstream medical applications when using transfer learning. Materials and Methods: This retrospective study included patients who underwent a radiologic study between 2005 and 2020 at an outpatient imaging facility. Key images and associated labels from the studies were retrospectively extracted from the original study interpretation. These images were used for RadImageNet model training with random weight initiation. The RadImageNet models were compared with ImageNet models using the area under the receiver operating characteristic curve (AUC) for eight classification tasks and using Dice scores for two segmentation problems. Results: The RadImageNet database consists of 1.35 million annotated medical images in 131 872 patients who underwent CT, MRI, and US for musculoskeletal, neurologic, oncologic, gastrointestinal, endocrine, abdominal, and pulmonary pathologic conditions. For transfer learning tasks on small datasets-thyroid nodules (US), breast masses (US), anterior cruciate ligament injuries (MRI), and meniscal tears (MRI)-the RadImageNet models demonstrated a significant advantage (P < .001) to ImageNet models (9.4%, 4.0%, 4.8%, and 4.5% AUC improvements, respectively). For larger datasets-pneumonia (chest radiography), COVID-19 (CT), SARS-CoV-2 (CT), and intracranial hemorrhage (CT)-the RadImageNet models also illustrated improved AUC (P < .001) by 1.9%, 6.1%, 1.7%, and 0.9%, respectively. Additionally, lesion localizations of the RadImageNet models were improved by 64.6% and 16.4% on thyroid and breast US datasets, respectively. Conclusion: RadImageNet pretrained models demonstrated better interpretability compared with ImageNet models, especially for smaller radiologic datasets.Keywords: CT, MR Imaging, US, Head/Neck, Thorax, Brain/Brain Stem, Evidence-based Medicine, Computer Applications-General (Informatics) Supplemental material is available for this article. Published under a CC BY 4.0 license.See also the commentary by Cadrin-Chênevert in this issue.

U-Net Based Segmentation and Characterization of Gliomas.

(1) Background: Gliomas are the most common primary brain neoplasms accounting for roughly 40−50% of all malignant primary central nervous system tumors. We aim to develop a deep learning-based framework for automated segmentation and prediction of biomarkers and prognosis in patients with gliomas. (2) Methods: In this retrospective two center study, patients were included if they (1) had a diagnosis of glioma with known surgical histopathology and (2) had preoperative MRI with FLAIR sequence. The entire tumor volume including FLAIR hyperintense infiltrative component and necrotic and cystic components was segmented. Deep learning-based U-Net framework was developed based on symmetric architecture from the 512 × 512 segmented maps from FLAIR as the ground truth mask. (3) Results: The final cohort consisted of 208 patients with mean ± standard deviation of age (years) of 56 ± 15 with M/F of 130/78. DSC of the generated mask was 0.93. Prediction for IDH-1 and MGMT status had a performance of AUC 0.88 and 0.62, respectively. Survival prediction of <18 months demonstrated AUC of 0.75. (4) Conclusions: Our deep learning-based framework can detect and segment gliomas with excellent performance for the prediction of IDH-1 biomarker status and survival.

Impact of COVID-19 social distancing regulations on outpatient diagnostic imaging volumes and no-show rates.

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.

Multidisciplinary management of metastatic spine disease: initial symptom-directed management.

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.

Incidental COVID-19 related lung apical findings on stroke CTA during the COVID-19 pandemic.

BACKGROUND: Authors 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. OBJECTIVE: To evaluate the incidence of these CTA findings and their relation to COVID-19 infection. METHODS: In 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. RESULTS: The 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. CONCLUSION: The 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.

Sacral Fractures and Sacroplasty.

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.

Machine learning for semi-automated classification of glioblastoma, brain metastasis and central nervous system lymphoma using magnetic resonance advanced imaging.

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.

MRA versus DSA for the follow-up imaging of intracranial aneurysms treated using endovascular techniques: a meta-analysis.

BACKGROUND: Treated 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. METHODS: Comprehensive 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. RESULTS: The 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%. CONCLUSION: MRA 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.

Predictive Factors and Rates of Fusion in Minimally Invasive Transforaminal Lumbar Interbody Fusion Utilizing rhBMP-2 or Mesenchymal Stem Cells.

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.

Spine Oncology: Imaging and Intervention.

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.

Interval Change in Diffusion and Perfusion MRI Parameters for the Assessment of Pseudoprogression in Cerebral Metastases Treated With Stereotactic Radiation.

OBJECTIVE: 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. MATERIALS AND METHODS: 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 (Ktrans), and DSC-MRI-derived relative cerebral blood volume (CBV) from pre- and post-SRS MRI scans were compared between groups using univariate and regression analysis. Fisher exact test was used to compare interval change of imaging biomarkers. RESULTS: Of 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), Ktrans (24/32 lesions; 75%; p = 0.006; odds ratio, 19.2), and relative CBV (27/32 lesions; 84%; p = 0.001; odds ratio, 25.3). CONCLUSION: Pseudoprogression can be distinguished from disease progression in cerebral metastases treated with SRS via an interval decrease in relative CBV and Ktrans values.

Optical Coherence Tomography in the Management of Skull Base Fibrous Dysplasia with Optic Nerve Involvement.

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.

Effects of Liposomal Bupivacaine With Adductor Canal Block on Pain and Functional Outcomes in Patients Undergoing Total Knee Arthroplasty.

BACKGROUND: Liposomal bupivacaine (LB) has an extended duration of action compared to bupivacaine and may allow patients to reach physical therapy (PT) goals faster than traditional methods. OBJECTIVE: To determine the effect of a periarticular LB mixture with adductor canal blockade (ACB) on postoperative opioid requirements, pain scores, and functional outcomes in patients undergoing primary unilateral total knee arthroplasty. METHODS: A retrospective chart review was performed; 86 patients received the LB mixture + ACB, and 86 historical controls received nonliposomal bupivacaine and femoral nerve block (FNB). RESULTS: There was no effect of group on mean postoperative pain scores (P = 0.144). There was an effect of group on equivalent morphine dose (P = 0.008). Pain scores and morphine doses changed over time in both groups, but there was no time-group interaction. Compared with controls, patients in the LB mixture group were more likely to require minimal assistance or better when going from a sitting to a standing position by postoperative day 1 (POD; 99% vs 81%, P = 0.0001) and POD 2 (90% vs 77%, P = 0.0212). There were no differences between groups with regard to discharge disposition or safety outcomes. Use did not affect LOS for patients discharged to an extended care facility but did reduce LOS for those discharged home. CONCLUSIONS: The LB mixture was effective in reducing opioid use and improving functional outcomes compared with historical controls.

Contrast-Enhanced Dixon Fat-Water Separation Imaging of the Spine: Added Value of Fat, In-Phase and Opposed-Phase Imaging in Marrow Lesion Detection.

OBJECTIVE: 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. METHODS: A retrospective cohort study of 36 subjects with focal spine lesions imaged with FWD was evaluated qualitatively and quantitatively. RESULTS: 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. CONCLUSIONS: 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.

CT of Anatomic Variants of the Paranasal Sinuses and Nasal Cavity: Poor Correlation With Radiologically Significant Rhinosinusitis but Importance in Surgical Planning.

OBJECTIVE: The purpose of this study was to determine the incidence of sinonasal anatomic variants and to assess their relation to sinonasal mucosal disease. MATERIALS AND METHODS: A retrospective evaluation of 192 sinus CT examinations of patients with a clinical history of rhinosinusitis was conducted. The CT scans were evaluated for the presence of several anatomic variants of the sinonasal cavities, and the prevalence of each variant was calculated. Prevalences of all sinonasal anatomic variants were compared between patients who had minimal to no apparent imaging evidence of rhinosinusitis and those who had radiologic evidence of clinically significant rhinosinusitis. RESULTS: The most common normal variants were nasal septal deviation, Agger nasi cells, and extension of the sphenoid sinuses into the posterior nasal septum. We found no statistically significant difference in the prevalence of any of the studied anatomic variants between patients with minimal and those with clinically significant paranasal sinus or nasal cavity disease. CONCLUSION: Analysis of every routine CT scan of the paranasal sinuses obtained for sinusitis or rhinitis for the presence of different anatomic variants is of questionable value unless surgery is planned.

An update to the Raymond-Roy Occlusion Classification of intracranial aneurysms treated with coil embolization.

BACKGROUND: 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. METHODS: 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. RESULTS: Class IIIa aneurysms were more likely to improve to Class I or II than Class IIIb aneurysms (83.34% vs 14.89%, p<0.001) and were also more likely than Class II to improve to Class I (52.78% vs 16.90%, p<0.001). Class IIIb aneurysms were more likely to remain incompletely occluded than Class IIIa aneurysms (85.11% vs 16.67%, p<0.001). 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%, p<0.001) and a trend toward higher subsequent rupture rate (3.23% vs 0.00%, p=0.068). CONCLUSIONS: 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.