Amish Doshi

Imaging and intervention for spinal facetogenic pain has evolved continuously, with radiologists at the helm of several new advanced techniques including CT-guided interventions to ensure accurate needle placement, biologic therapies including platelet-rich plasma, and new noninvasive therapies such as MR-guided focused ultrasound. Though advances have been made in both imaging localization of painful facet joints and therapies offered, awareness of these techniques and the reimbursement landscape are varied. We hope to elucidate the current state of practice for both diagnosis and treatment of this common painful ailment, and highlight the ways that radiologists are at the forefront of advancement in these techniques.

Objective To identify predictors for time to first treatment modality (TTT) in patients diagnosed with spinal metastatic disease. Methods Our radiology database was retrospectively queried to identify patients with spinal metastases (01/2017-12/2021). Demographics, setting of initial imaging (inpatient/outpatient/ED), histology, treatment modality, and TTT were collected. Several different early TTT thresholds were explored (≤ 30, ≤ 21, ≤14, and ≤ 7 days). After controlling for age, gender, diagnostic setting, pathology, type of treatment multivariable linear and logistic regressions were performed for the primary and secondary thresholds at different time-points. Results A total of 1009 patients with spinal metastases were included, with a median age of 65 years (IQR 15) and 529 (52.4%) males. Diagnoses occurred in the inpatient (37%), outpatient (50%), and emergency department (13%) settings. The most common primary tumors were breast (22.4%), prostate (19.5%), and non-small cell lung cancer (12.8%). Treatment modalities included surgery (14.6%), chemotherapy (54.5%), and radiation therapy (43.5%). The median time to treatment (TTT) was 13 days (SD 27, range 0–676), with no significant difference by setting (p = 0.2). In multivariable linear regression, surgery was associated with shorter TTT (p = 0.037). Logistic regression using different early-TTT thresholds identified age, surgical intervention, lymphoma, and outpatient setting as significant predictors across models. Sensitivity analyses excluding TTT outliers showed that surgery was no longer a significant predictor, while other covariates remained stable. Conclusions Surgical intervention and lymphoma independently predicted earlier TTT of any modality in spinal metastases, whereas older age and outpatient diagnosis were associated with delays.

“Just Accepted” papers have undergone full peer review and have been accepted for publication in Radiology: Artificial Intelligence. This article will undergo copyediting, layout, and proof review ...

The ASNR Neuroradiology Division Chief Working Group9s 2023 survey, with responses from 62 division chiefs, provides insights into turn-around times, faculty recruitment, moonlighting opportunities, and academic funds. In emergency cases, 61% aim for a turn-around time of less than 45-60 minutes, with two-thirds meeting this expectation more than 75% of the time. For inpatient CT and MRI scans, 54% achieve a turn-around time of 4-8 hours, with three quarters meeting this expectation at least 50% of the time. Outpatient scans have an expected turn-around time of 24-48 hours, which is met in 50% of cases. Faculty recruitment strategies included 35% offering sign-on bonuses, with a median of $30,000. Additionally, 23% provided bonuses to fellows during fellowship to retain them in the practice upon completion of their fellowship. Internal moonlighting opportunities for faculty were offered by 70% of divisions, with a median pay of $250 per hour. The median annual academic fund for a full-time neuroradiology faculty member was $6,000, typically excluding license fees but including ACR and ABR membership, leaving $4,000 for professional expenses. This survey calls for further dialogue on adapting and innovating academic institutions to meet evolving needs in neuroradiology.

(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.

OBJECTIVES Examine age differences in SARS-CoV-2 transmission risk from primary cases and infection risk among household contacts, and symptoms among those with SARS-CoV-2 infection. METHODS People with SARS-CoV-2 infection in Nashville, Tennessee and central and western Wisconsin and their household contacts were followed daily for 14 days to ascertain symptoms and secondary transmission events. Households were enrolled between April 2020 and April 2021. Secondary infection risks (SIR) by age of the primary case and contacts were estimated using generalized estimating equations. RESULTS The 226 primary cases were followed by 197 (49%) secondary SARS-CoV-2 infections among 404 household contacts. Age group-specific SIR among contacts ranged from 35% to 53%, with no differences by age. SIR was lower from primary cases aged 12-17 years than from primary cases 18-49 years (risk ratio [RR] 0.42; 95% confidence interval [CI] 0.19-0.92). SIR was 56% and 45%, respectively, among primary case-contact pairs in the same versus different age group (RR 1.54; 95% CI 1.03-2.31). SIR was highest among primary case-contacts pairs aged ≥65 years (77%) and 5-11 years (70%). Among secondary SARS-CoV-2 infections, 19% were asymptomatic; there was no difference in the frequency of asymptomatic infections by age group. CONCLUSIONS Both children and adults can transmit and are susceptible to SARS-CoV-2 infection. SIR did not vary by age, but further research is needed to understand age-related differences in probability of transmission from primary cases by age.

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.