Recommendations for Additional Imaging on Head and Neck Imaging Examinations: Interradiologist Variation and Associated Factors.

BACKGROUND. A paucity of relevant guidelines may lead to pronounced variation among radiologists in issuing recommendations for additional imaging (RAI) for head and neck imaging. OBJECTIVE. The purpose of this article was to explore associations of RAI for head and neck imaging examinations with examination, patient, and radiologist factors and to assess the role of individual radiologist-specific behavior in issuing such RAI. METHODS. This retrospective study included 39,200 patients (median age, 58 years; 21,855 women, 17,315 men, 30 with missing sex information) who underwent 39,200 head and neck CT or MRI examinations, interpreted by 61 radiologists, from June 1, 2021, through May 31, 2022. A natural language processing (NLP) tool with manual review of NLP results was used to identify RAI in report impressions. Interradiologist variation in RAI rates was assessed. A generalized mixed-effects model was used to assess associations between RAI and examination, patient, and radiologist factors. RESULTS. A total of 2943 (7.5%) reports contained RAI. Individual radiologist RAI rates ranged from 0.8% to 22.0% (median, 7.1%; IQR, 5.2-10.2%), representing a 27.5-fold difference between minimum and a maximum values and 1.8-fold difference between 25th and 75th percentiles. In multivariable analysis, RAI likelihood was higher for CTA than for CT examinations (OR, 1.32), for examinations that included a trainee in report generation (OR, 1.23), and for patients with self-identified race of Black or African American versus White (OR, 1.25); was lower for male than female patients (OR, 0.90); and was associated with increasing patient age (OR, 1.09 per decade) and inversely associated with radiologist years since training (OR, 0.90 per 5 years). The model accounted for 10.9% of the likelihood of RAI. Of explainable likelihood of RAI, 25.7% was attributable to examination, patient, and radiologist factors; 74.3% was attributable to radiologist-specific behavior. CONCLUSION. Interradiologist variation in RAI rates for head and neck imaging was substantial. RAI appear to be more substantially associated with individual radiologist-specific behavior than with measurable systemic factors. CLINICAL IMPACT. Quality improvement initiatives, incorporating best practices for incidental findings management, may help reduce radiologist preference-sensitive decision-making in issuing RAI for head and neck imaging and associated care variation.

Improved optic nerve visualization and treatment planning through a dedicated optic nerve MRI protocol.

OBJECTIVE: This study describes an innovative optic nerve MRI protocol for better delineating optic nerve anatomy from neighboring pathology. METHODS: Twenty-two patients undergoing MRI examination of the optic nerve with the dedicated protocol were identified and included for analysis of imaging, surgical strategy, and outcomes. T2-weighted and fat-suppressed T1-weighted gadolinium-enhanced images were acquired perpendicular and parallel to the long axis of the optic nerve to achieve en face and in-line views along the course of the nerve. RESULTS: Dedicated optic nerve MRI sequences provided enhanced visualization of the nerve, CSF within the nerve sheath, and local pathology. Optic nerve sequences leveraged the "CSF ring" within the optic nerve sheath to create contrast between pathology and normal tissue, highlighting areas of compression. Tumor was readily tracked along the longitudinal axis of the nerve by images obtained parallel to the nerve. The findings augmented treatment planning. CONCLUSIONS: The authors present a dedicated optic nerve MRI protocol that is simple to use and affords improved cross-sectional and longitudinal visualization of the nerve, surrounding CSF, and pathology. This improved visualization enhances radiological evaluation and treatment planning for optic nerve lesions.

Neuroimaging-based classification of PTSD using data-driven computational approaches: A multisite big data study from the ENIGMA-PGC PTSD consortium.

BACKGROUND: Recent advances in data-driven computational approaches have been helpful in devising tools to objectively diagnose psychiatric disorders. However, current machine learning studies limited to small homogeneous samples, different methodologies, and different imaging collection protocols, limit the ability to directly compare and generalize their results. Here we aimed to classify individuals with PTSD versus controls and assess the generalizability using a large heterogeneous brain datasets from the ENIGMA-PGC PTSD Working group. METHODS: We analyzed brain MRI data from 3,477 structural-MRI; 2,495 resting state-fMRI; and 1,952 diffusion-MRI. First, we identified the brain features that best distinguish individuals with PTSD from controls using traditional machine learning methods. Second, we assessed the utility of the denoising variational autoencoder (DVAE) and evaluated its classification performance. Third, we assessed the generalizability and reproducibility of both models using leave-one-site-out cross-validation procedure for each modality. RESULTS: We found lower performance in classifying PTSD vs. controls with data from over 20 sites (60 % test AUC for s-MRI, 59 % for rs-fMRI and 56 % for d-MRI), as compared to other studies run on single-site data. The performance increased when classifying PTSD from HC without trauma history in each modality (75 % AUC). The classification performance remained intact when applying the DVAE framework, which reduced the number of features. Finally, we found that the DVAE framework achieved better generalization to unseen datasets compared with the traditional machine learning frameworks, albeit performance was slightly above chance. CONCLUSION: These results have the potential to provide a baseline classification performance for PTSD when using large scale neuroimaging datasets. Our findings show that the control group used can heavily affect classification performance. The DVAE framework provided better generalizability for the multi-site data. This may be more significant in clinical practice since the neuroimaging-based diagnostic DVAE classification models are much less site-specific, rendering them more generalizable.

Diagnostic performance of computed tomography features in detecting oropharyngeal squamous cell carcinoma extranodal extension.

OBJECTIVES: Accurate pre-treatment imaging determination of extranodal extension (ENE) could facilitate the selection of appropriate initial therapy for HPV-positive oropharyngeal squamous cell carcinoma (HPV + OPSCC). Small studies have associated 7 CT features with ENE with varied results and agreement. This article seeks to determine the replicable diagnostic performance of these CT features for ENE. METHODS: Five expert academic head/neck neuroradiologists from 5 institutions evaluate a single academic cancer center cohort of 75 consecutive HPV + OPSCC patients. In a web-based virtual laboratory for imaging research and education, the experts performed training on 7 published CT features associated with ENE and then independently identified the "single most (if any) suspicious" lymph node and presence/absence of each of the features. Inter-rater agreement was assessed using percentage agreement, Gwet's AC1, and Fleiss' kappa. Sensitivity, specificity, and positive and negative predictive values were calculated for each CT feature based on histologic ENE. RESULTS: All 5 raters identified the same node in 52 cases (69%). In 15 cases (20%), at least one rater selected a node and at least one rater did not. In 8 cases (11%), all raters selected a node, but at least one rater selected a different node. Percentage agreement and Gwet's AC1 coefficients were > 0.80 for lesion identification, matted/conglomerated nodes, and central necrosis. Fleiss' kappa was always < 0.6. CT sensitivity for histologically confirmed ENE ranged 0.18-0.94, specificity 0.41-0.88, PPV 0.26-0.36, and NPV 0.78-0.96. CONCLUSIONS: Previously described CT features appear to have poor reproducibility among expert head/neck neuroradiologists and poor predictive value for histologic ENE. KEY POINTS: • Previously described CT imaging features appear to have poor reproducibility among expert head and neck subspecialized neuroradiologists as well as poor predictive value for histologic ENE. • Although it may still be appropriate to comment on the presence or absence of these CT features in imaging reports, the evidence indicates that caution is warranted when incorporating these features into clinical decision-making regarding the likelihood of ENE.

Predictors of Completion of Clinically Necessary Radiologist-Recommended Follow-Up Imaging: Assessment Using an Automated Closed-Loop Communication and Tracking Tool.

BACKGROUND. Patients with adverse social determinants of health may be at increased risk of not completing clinically necessary follow-up imaging. OBJECTIVE. The purpose of this study was to use an automated closed-loop communication and tracking tool to identify patient-, referrer-, and imaging-related factors associated with lack of completion of radiologist-recommended follow-up imaging. METHODS. This retrospective study was performed at a single academic health system. A tool for automated communication and tracking of radiologist-recommended follow-up imaging was embedded in the PACS and electronic health record. The tool prompted referrers to record whether they deemed recommendations to be clinically necessary and assessed whether clinically necessary follow-up imaging was pursued. If imaging was not performed within 1 month after the intended completion date, the tool prompted a safety net team to conduct further patient and referrer follow-up. The study included patients for whom a follow-up imaging recommendation deemed clinically necessary by the referrer was entered with the tool from October 21, 2019, through June 30, 2021. The electronic health record was reviewed for documentation of eventual completion of the recommended imaging at the study institution or an outside institution. Multivariable logistic regression analysis was performed to identify factors associated with completion of follow-up imaging. RESULTS. Of 5856 recommendations entered during the study period, the referrer agreed with 4881 recommendations in 4599 patients (2929 women, 1670 men; mean age, 61.3 ± 15.6 years), who formed the study sample. Follow-up was completed for 74.8% (3651/4881) of recommendations. Independent predictors of lower likelihood of completing follow-up imaging included living in a socioeconomically disadvantaged neighborhood according to the area deprivation index (odds ratio [OR], 0.67 [95% CI, 0.54-0.84]), inpatient (OR, 0.25 [95% CI, 0.20-0.32]) or emergency department (OR, 0.09 [95% CI, 0.05-0.15]) care setting, and referrer surgical specialty (OR, 0.70 [95% CI, 0.58-0.84]). Patient age, race and ethnicity, primary language, and insurance status were not independent predictors of completing follow-up (p > .05). CONCLUSION. Socioeconomically disadvantaged patients are at increased risk of not completing recommended follow-up imaging that referrers deem clinically necessary. CLINICAL IMPACT. Initiatives for ensuring completion of follow-up imaging should be aimed at the identified patient groups to reduce disparities in missed and delayed diagnoses.

Development and External Validation of an Artificial Intelligence Model for Identifying Radiology Reports Containing Recommendations for Additional Imaging.

BACKGROUND. Reported rates of recommendations for additional imaging (RAIs) in radiology reports are low. Bidirectional encoder representations from transformers (BERT), a deep learning model pretrained to understand language context and ambiguity, has potential for identifying RAIs and thereby assisting large-scale quality improvement efforts. OBJECTIVE. The purpose of this study was to develop and externally validate an artificial intelligence (AI)-based model for identifying radiology reports containing RAIs. METHODS. This retrospective study was performed at a multisite health center. A total of 6300 radiology reports generated at one site from January 1, 2015, to June 30, 2021, were randomly selected and split by 4:1 ratio to create training (n = 5040) and test (n = 1260) sets. A total of 1260 reports generated at the center's other sites (including academic and community hospitals) from April 1 to April 30, 2022, were randomly selected as an external validation group. Referring practitioners and radiologists of varying sub-specialties manually reviewed report impressions for presence of RAIs. A BERT-based technique for identifying RAIs was developed by use of the training set. Performance of the BERT-based model and a previously developed traditional machine learning (TML) model was assessed in the test set. Finally, performance was assessed in the external validation set. The code for the BERT-based RAI model is publicly available. RESULTS. Among a total of 7419 unique patients (4133 women, 3286 men; mean age, 58.8 years), 10.0% of 7560 reports contained RAI. In the test set, the BERT-based model had 94.4% precision, 98.5% recall, and an F1 score of 96.4%. In the test set, the TML model had 69.0% precision, 65.4% recall, and an F1 score of 67.2%. In the test set, accuracy was greater for the BERT-based than for the TML model (99.2% vs 93.1%, p < .001). In the external validation set, the BERT-based model had 99.2% precision, 91.6% recall, an F1 score of 95.2%, and 99.0% accuracy. CONCLUSION. The BERT-based AI model accurately identified reports with RAIs, outperforming the TML model. High performance in the external validation set suggests the potential for other health systems to adapt the model without requiring institution-specific training. CLINICAL IMPACT. The model could potentially be used for real-time EHR monitoring for RAIs and other improvement initiatives to help ensure timely performance of clinically necessary recommended follow-up.

Iatrogenic inner ear dehiscence associated with lateral skull base surgery: a systematic analysis of drilling injuries and their causal factors.

PURPOSE: Drilling injuries of the inner ear are an underreported complication of lateral skull base (LSB) surgery. Inner ear breaches can cause hearing loss, vestibular dysfunction, and third window phenomenon. This study aims to elucidate primary factors causing iatrogenic inner ear dehiscences (IED) in 9 patients who presented to a tertiary care center with postoperative symptoms of IED following LSB surgery for vestibular schwannoma, endolymphatic sac tumor, Meniere's disease, paraganglioma jugulare, and vagal schwannoma. METHODS: Utilizing 3D Slicer image processing software, geometric and volumetric analysis was applied to both preoperative and postoperative imaging to identify causal factors iatrogenic inner ear breaches. Segmentation analyses, craniotomy analyses, and drilling trajectory analyses were performed. Cases of retrosigmoid approaches for vestibular schwannoma resection were compared to matched controls. RESULTS: Excessive lateral drilling and breach of a single inner ear structure occurred in 3 cases undergoing transjugular (n=2) and transmastoid (n=1) approaches. Inadequate drilling trajectory breaching ≥1 inner ear structure occurred in 6 cases undergoing retrosigmoid (n=4), transmastoid (n=1), and middle cranial fossa approaches (n=1). In retrosigmoid approaches the 2-cm visualization window and craniotomy limits did not provide drilling angles to the entire tumor without causing IED in comparison to matched controls. CONCLUSIONS: Inappropriate drill depth, errant lateral drilling, inadequate drill trajectory, or a combination of these led to iatrogenic IED. Image-based segmentation, individualized 3D anatomical model generation, and geometric and volumetric analyses can optimize operative plans and possibly reduce inner ear breaches from lateral skull base surgery.

A relaxometry method that emphasizes practicality and availability.

PURPOSE: Although many methods have been proposed to quantitatively map the main MRI parameters (e.g., T1 , T2 , C × M0 ), these methods often involve special sequences not readily available on clinical scanners and/or may require long scan times. In contrast, the proposed method can readily run on most scanners, offer flexible tradeoffs between scan time and image quality, and map MRI parameters jointly to ensure spatial alignment. METHODS: The approach is based on the multi-shot spin-echo (SE) EPI sequence. The corresponding signal equation was derived and strategies for solving it were developed. As usual with multi-shot EPI, scan time can readily be traded-off against image quality by adjusting the echo train length. Validation was performed against reference relaxometry methods, in gel phantoms with varying concentrations of gadobutrol and gadoterate meglumine contrast agents. In vivo examples are further presented, from 3 neuroradiology patients. RESULTS: Bland-Altman analysis was performed: for T2 , as compared to 2D SE, bias was 0.29 ms and the 95% limits of agreement ranged from -1.15 to +1.73 ms. For T1 , compared to inversion-recovery SE (and MOLLI), bias was -20.2 ms (and -14.5 ms) and the limits of agreement ranged from -62.4 to +22.0 ms (and -53.8 to +24.9 ms). The mean relative T1 error between the proposed method and each of the 2 reference methods was similar to that of the reference methods among themselves. CONCLUSION: In the constellation of existing relaxometry methods, the proposed method is meant to stand out in terms of its practicality and availability.

Altered white matter microstructural organization in posttraumatic stress disorder across 3047 adults: results from the PGC-ENIGMA PTSD consortium.

A growing number of studies have examined alterations in white matter organization in people with posttraumatic stress disorder (PTSD) using diffusion MRI (dMRI), but the results have been mixed which may be partially due to relatively small sample sizes among studies. Altered structural connectivity may be both a neurobiological vulnerability for, and a result of, PTSD. In an effort to find reliable effects, we present a multi-cohort analysis of dMRI metrics across 3047 individuals from 28 cohorts currently participating in the PGC-ENIGMA PTSD working group (a joint partnership between the Psychiatric Genomics Consortium and the Enhancing NeuroImaging Genetics through Meta-Analysis consortium). Comparing regional white matter metrics across the full brain in 1426 individuals with PTSD and 1621 controls (2174 males/873 females) between ages 18-83, 92% of whom were trauma-exposed, we report associations between PTSD and disrupted white matter organization measured by lower fractional anisotropy (FA) in the tapetum region of the corpus callosum (Cohen's d = -0.11, p = 0.0055). The tapetum connects the left and right hippocampus, for which structure and function have been consistently implicated in PTSD. Results were consistent even after accounting for the effects of multiple potentially confounding variables: childhood trauma exposure, comorbid depression, history of traumatic brain injury, current alcohol abuse or dependence, and current use of psychotropic medications. Our results show that PTSD may be associated with alterations in the broader hippocampal network.

Image quality comparisons of coil setups in 3T MRI for brain and head and neck radiotherapy simulations.

PURPOSE: MRI is increasingly used for brain and head and neck radiotherapy treatment planning due to its superior soft tissue contrast. Flexible array coils can be arranged to encompass treatment immobilization devices, which do not fit in diagnostic head/neck coils. Selecting a flexible coil arrangement to replace a diagnostic coil should rely on image quality characteristics and patient comfort. We compared image quality obtained with a custom UltraFlexLarge18 (UFL18) coil setup against a commercial FlexLarge4 (FL4) coil arrangement, relative to a diagnostic Head/Neck20 (HN20) coil at 3T. METHODS: The large American College of Radiology (ACR) MRI phantom was scanned monthly in the UFL18, FL4, and HN20 coil setup over 2 years, using the ACR series and three clinical sequences. High-contrast spatial resolution (HCSR), image intensity uniformity (IIU), percent-signal ghosting (PSG), low-contrast object detectability (LCOD), signal-to-noise ratio (SNR), and geometric accuracy were calculated according to ACR recommendations for each series and coil arrangement. Five healthy volunteers were scanned with the clinical sequences in all three coil setups. SNR, contrast-to-noise ratio (CNR) and artifact size were extracted from regions-of-interest along the head for each sequence and coil setup. For both experiments, ratios of image quality parameters obtained with UFL18 or FL4 over those from HN20 were formed for each coil setup, grouping the ACR and clinical sequences. RESULTS: Wilcoxon rank-sum tests revealed significantly higher (p < 0.001) LCOD, IIU and SNR, and lower PSG ratios with UFL18 than FL4 on the phantom for the clinical sequences, with opposite PSG and SNR trends for the ACR series. Similar statistical tests on volunteer data corroborated that SNR ratios with UFL18 (0.58 ± 0.19) were significantly higher (p < 0.001) than with FL4 (0.51 ± 0.18) relative to HN20. CONCLUSIONS: The custom UFL18 coil setup was selected for clinical application in MR simulations due to the superior image quality demonstrated on a phantom and volunteers for clinical sequences and increased volunteer comfort.

The T2-FLAIR mismatch sign as a predictor of IDH-mutant, 1p/19q-noncodeleted lower-grade gliomas: a systematic review and diagnostic meta-analysis.

OBJECTIVES: To evaluate the diagnostic performance of the T2-FLAIR mismatch sign for prediction of isocitrate dehydrogenase (IDH)-mutant, 1p/19q-noncodeleted lower-grade gliomas (LGGs) and review studies with false positive results. METHODS: The MEDLINE and EMBASE databases were searched up to March 13, 2020, to identify articles reporting the diagnostic performance of the T2-FLAIR mismatch sign for prediction of IDH-mutant, 1p/19q-noncodeleted LGGs (IDHmut-Noncodel) using the search terms (T2 FLAIR mismatch). Pooled sensitivity, specificity, and correlation coefficient for interobserver agreement were calculated. RESULTS: Twelve studies including a total of 1053 patients were included. The median age was 43 (median; range, 14-56). The pooled sensitivity and specificity were 42% (95% CI, 28-58%) and 100% (95% CI, 88-100%), respectively. According to the HSROC curve, the area under the curve was 0.77 (95% CI, 0.73-0.80). Considerable heterogeneity was possible among the studies in terms of both sensitivity and specificity. A threshold effect was suggested and was considered to explain most of the heterogeneity. Four studies reported false positive results for the T2-FLAIR mismatch sign, including dysembryoplastic neuroepithelial tumor, pediatric-type gliomas, and non-neoplastic lesions. The 2 original articles with false positive results showed the highest sensitivities among the 10 studies included in the quantitative analysis, supporting the probability of the threshold effect. The pooled correlation coefficient was 0.87 (95% CI, 0.73-0.94). CONCLUSIONS: The T2-FLAIR mismatch sign had a high specificity and interobserver agreement for the prediction of IDHmut-Noncodel. However, the sign demonstrated low sensitivity, and a few studies with false positive cases were also reported. KEY POINTS: • The pooled sensitivity and specificity of the T2-FLAIR mismatch sign for prediction of IDH-mutant, 1p/19q-noncodeleted lower-grade gliomas were 42% and 100%, respectively. • Four studies reported false positive results. • The pooled correlation coefficient was 0.87, suggesting almost perfect interobserver agreement.

The diagnostic performance of CT and MRI for detecting extranodal extension in patients with head and neck squamous cell carcinoma: a systematic review and diagnostic meta-analysis.

OBJECTIVE: To review the diagnostic performance of CT and MRI for detecting extranodal extension (ENE) in head and neck squamous cell carcinoma (HNSCC) patients. METHODS: MEDLINE and EMBASE databases were searched up to October 7, 2019. Studies that evaluated the diagnostic performance of CT and/or MRI for detecting ENE in HNSCC patients were included. A 2 × 2 table was reconstructed for each study. Pooled sensitivity and specificity were calculated using the bivariate model and hierarchical summary receiver operating characteristic (HSROC) model. Subgroup analyses were performed according to HPV status and radiological features. Pooled correlation coefficient for interobserver agreement was calculated. RESULTS: Twenty-two studies including 2478 patients were included. The pooled sensitivity and specificity for detecting ENE were 73% (95% CI, 62-82%) and 83% (95% CI, 75-89%), respectively, for CT, and 60% (95% CI, 49-70%) and 96% (95% CI, 85-99%), respectively, for MRI. There was substantial heterogeneity for both CT and MRI. A threshold effect was present for MRI. On subgroup analysis, the pooled specificity of CT was significantly lower in patients with HPV+ OPSCC than in patients with HPV­ oral cavity cancer or all HNSCC (74% vs. 87%; p = 0.01). Central node necrosis showed significantly higher pooled sensitivity (81% vs. 51%; p = 0.02), while infiltration of adjacent planes showed significantly higher pooled specificity (94% vs. 65%; p = 0.03). The pooled correlation coefficient was 0.72 (95% CI, 0.60-0.81). CONCLUSION: Both CT and MRI show reasonable diagnostic performance for detecting ENE in HNSCC patients and interobserver agreement was substantial. KEY POINTS: • Pooled sensitivity and specificity were 73% and 83% for CT and 60% and 96% for MRI without significant difference. • Pooled specificity was lower for HPV+ OPSCC than for HPV­ oral cavity cancer or all HNSCC (74% vs. 87%, p = 0.01), likely due to central node necrosis. • Central node necrosis showed higher sensitivity (81% vs. 51%; p = 0.02), while infiltration of adjacent planes showed higher specificity (94% vs. 65%; p = 0.03).

Immune checkpoint inhibitor therapy may increase the incidence of treatment-related necrosis after stereotactic radiosurgery for brain metastases: a systematic review and meta-analysis.

OBJECTIVES: To compare the incidence of treatment-related necrosis between combination SRS+ICI therapy and SRS therapy alone in patients with brain metastases from melanoma and non-small cell lung cancer (NSCLC). METHODS: A systematic literature search of Ovid-MEDLINE and EMBASE was performed up to August 10, 2020. The difference in the pooled incidence of treatment-related necrosis after SRS+ICI or SRS alone was evaluated. The cumulative incidence of treatment-related necrosis at the specific time point after the treatment was calculated and plotted. Subgroup and meta-regression analyses were additionally performed. RESULTS: Sixteen studies (14 on melanoma, 2 on NSCLC) were included. In NSCLC brain metastasis, the reported incidences of treatment-related necrosis in SRS+ICI and SRS alone ranged 2.9-3.4% and 0-2.9%, respectively. Meta-analysis was conducted including 14 studies on melanoma brain metastasis. The incidence of treatment-related necrosis was higher in SRS+ICI than SRS alone (16.0% vs. 6.5%; p = 0.065; OR, 2.35). The incidence showed rapid increase until 12 months after the SRS when combined with ICI therapy (14%; 95% CI, 8-22%) and its pace of increase slowed thereafter. Histopathologic diagnosis as the reference standard for treatment-related necrosis and inclusion of only symptomatic cases were the source of heterogeneity in SRS+ICI. CONCLUSIONS: Treatment-related necrosis tended to occur 2.4 times more frequently in the setting of combination SRS+ICI therapy compared with SRS alone in melanoma brain metastasis showing high cumulative incidence within the first year. Treatment-related necrosis should be considered when SRS+ICI combination therapy is used for melanoma brain metastasis, especially in the first year. KEY POINTS: • Treatment-related necrosis occurred 2.4 times more frequently in the setting of combination SRS+ICI therapy compared with SRS alone in melanoma brain metastasis. • Treatment-related necrosis more frequently occurred in brain metastases from melanoma than NSCLC. • Reference standard for treatment-related necrosis and inclusion of only symptomatic treatment-related necrosis were a significant source of heterogeneity, indicating varying definitions of treatment-related necrosis in the literature need to be unified.

Diagnostic Yield of Body CT and Whole-Body FDG PET/CT for Initial Systemic Staging in Patients With Suspected Primary CNS Lymphoma: A Systematic Review and Meta-Analysis.

BACKGROUND. Several guidelines recommend body imaging for the initial work-up of patients with suspected primary CNS lymphoma, to exclude subclinical systemic involvement. However, to our knowledge, the diagnostic yield of body CT (contrast-enhanced CT of the chest, abdomen, and pelvis) and whole-body FDG PET/CT for the evaluation of subclinical systemic lymphoma has not yet been systematically evaluated. OBJECTIVE. The purpose of this study was to investigate and compare the diagnostic yield of body CT and whole-body FDG PET/CT in detecting subclinical systemic lymphoma in patients with suspected primary CNS lymphoma. EVIDENCE ACQUISITION. A systematic search of the MEDLINE and EMBASE databases through July 5, 2020, was conducted to identify studies evaluating the diagnostic yield of body CT or whole-body FDG PET/CT in detecting subclinical systemic lymphoma in patients with suspected primary CNS lymphoma. Pooled estimates of the diagnostic yield of both imaging modalities were calculated using the DerSimonian and Laird random-effects model. The false referral rate and the rate of incidental secondary malignancy were also pooled. EVIDENCE SYNTHESIS. Nine original articles on studies evaluating a total of 1040 patients were included. In detecting subclinical systemic lymphoma, the pooled diagnostic yields of body CT and whole-body FDG PET/CT were 2.5% (95% CI, 1.5-3.9%) and 4.9% (95% CI, 2.8-8.5%), respectively. In the subgroup analysis, the diagnostic yield of whole-body FDG PET/CT was significantly higher than that of body CT (p = .03). Four studies reported changes in the management plan: the R-CHOP (rituximab, cyclophosphamide, hydroxydaunorubicin, vincristine, and prednisone) regimen with or without radiation therapy was added if extracranial lymphoma involvement was detected by body CT or whole-body FDG PET/CT. The pooled false referral rate of whole-body FDG PET/CT was 5.3% (95% CI, 2.2-12.0%). The pooled rate of incidental secondary malignancy detected on whole-body FDG PET/CT was 3.1% (95% CI, 1.7-5.6%). CONCLUSION. Body imaging should be used in the initial workup of patients with suspected primary CNS lymphoma, to exclude systemic involvement. Whole-body FDG PET/CT may be a better alternative to body CT. CLINICAL IMPACT. Our results support current National Comprehensive Cancer Network guidelines for the use of body imaging to exclude subclinical systemic involvement in patients with suspected primary CNS lymphoma.

Development of Brain Metastases in Patients With Non-Small Cell Lung Cancer and No Brain Metastases at Initial Staging Evaluation: Cumulative Incidence and Risk Factor Analysis.

BACKGROUND. Although established guidelines give indications for performing staging brain MRI at initial diagnosis of non-small cell lung cancer (NSCLC), guidelines are lacking for performing surveillance brain MRI for patients without brain metastases at presentation. OBJECTIVE. The purpose of this study is to estimate the cumulative incidence of and risk factors for brain metastasis development in patients with NSCLC without brain metastases at initial presentation. METHODS. This retrospective study included 1495 patients with NSCLC (mean [± SD] age, 65 ± 10 years; 920 men and 575 women) without brain metastases at initial evaluation that included brain MRI. Follow-up brain MRI was ordered at the discretion of the referring physicians. MRI examinations were reviewed in combination with clinical records for brain metastasis development; patients not undergoing MRI were deemed to have not had metastases develop through last clinical follow-up. The cumulative incidence of brain metastases was determined, with death considered a competing risk, and was stratified by clinical stage group, cell type, and epidermal growth factor receptor (EGFR) gene mutation status. Univariable and multivariable Cox proportional hazards regression analyses were performed. RESULTS. A total of 258 of 1495 patients (17.3%) underwent follow-up brain MRI, and 72 (4.8%) had brain metastases develop at a median of 12.3 months after initial diagnosis of NSCLC. Of the 72 patients who had metastases develop, 44.4% had no neurologic symptoms, and 58.3% had stable primary thoracic disease. The cumulative incidence of brain metastases at 6, 12, 18, and 24 months after initial evaluation was 0.6%, 2.1%, 4.2%, and 6.8%, respectively. Cumulative incidence at 6, 12, 18, and 24 months was higher (p < .001) in patients with clinical stage III-IV disease (1.3%, 3.9%, 7.7%, and 10.9%, respectively) than in those with clinical stage I-II disease (0.0%, 0.8%, 1.2%, and 2.6%, respectively), and it was higher (p < .001) in patients with EGFR mutation-positive adenocarcinoma (0.7%, 2.5%, 6.3%, and 12.3%, respectively) than in those with EGFR mutation-negative adenocarcinoma (0.4%, 1.8%, 2.9%, and 4.4%, respectively). Among 1109 patients with adenocarcinoma, independent risk factors for the development of brain metastasis were clinical stage III-IV (hazard ratio [HR], 9.39; p < .001) and EGFR mutation-positive status (HR, 1.78; p = .04). The incidence of brain metastasis over the study interval was 8.7% among patients with clinical stage III-IV disease and 17.4% among those with EGFR mutation-positive adenocarcinoma. CONCLUSION. Clinical stage III-IV and EGFR mutation-positive adenocarcinoma are independent risk factors for brain metastasis development. CLINICAL IMPACT. For patients with clinical stage III-IV disease or EGFR mutation-positive adenocarcinoma, surveillance brain MRI performed 12 months after initial evaluation may be warranted.

The role of computed tomography angiography as initial imaging tool for acute hemorrhage in the head and neck.

OBJECTIVES: Acute hemorrhage in the head and neck (AHNH) is life-threatening due to asphyxiation and hemorrhagic shock. When conservative measures fail, some patients benefit from endovascular therapy (EVT). While CTA is routinely used to localize bleeding and plan EVT in gastrointestinal hemorrhage, the diagnostic value of CTA in AHNH and role of CTA in treatment-planning are uncertain. METHODS: We retrospectively reviewed neck CTAs from June 2015 to October 2018 indicated for AHNH. When performed, digital subtraction angiography (DSA) findings and EVT were documented. Extravasation or pseudoaneurysm on DSA was considered positive for bleed localization. RESULTS: Thirty CTA exams were performed for AHNH in 18 patients (mean age = 56.6, male% = 55.6%). Eleven out of 30 exams (36.7%) had immediate DSA follow-up within 24 h. Etiologies of hemorrhage included malignancy 11/18 (61.1%) and coagulopathy (4/18, 22.2%) among others. CTA reports identified definite or possible source of bleeding in 7/30 (23.3%) exams. Seven out of 7 (100%) patients with definite or possible source of bleeding on CTA underwent DSA and 4/23 (17.4%) patients underwent DSA despite negative CTA. With DSA as the gold standard, CTA had a sensitivity of 70% and a specificity of 100%. CONCLUSIONS: CTA has high specificity and reasonable sensitivity for detecting arterial source of bleeding in patients presenting with AHNH. Patients with negative CTA may avoid catheter angiography in most cases; however, false-negative CTA should not preclude angiography in high-risk patients.

Imaging of IgG4-Related Disease in the Head and Neck: A Systematic Review, Case Series, and Pathophysiology Update.

This systematic review aims to clarify and comprehensively detail the sometimes variable published imaging features as well as the pathogenesis, clinical diagnostic criteria, and treatment options of IgG4-Related Diseases (IgG4-RD) in the head and neck to aid the radiologist in diagnosing relapse and new sites of disease. A literature search in PubMed and EMBASE for reported cases of IgG4-RD was performed in December 2019. Case reports or series of IgG4-RD in the head and neck in adults that included sufficient imaging and pathology findings were included. This yielded 50 reports. IgG4-RD locations included the orbits, thyroid, pituitary gland, paranasal sinuses, salivary and parotid glands, larynx, pharynx, cervical lymph nodes, meninges, and skull base. Most lesions demonstrated non-specific homogenous CT attenuation, diffuse enhancement, isointense/low T2 signal intensity, and low T1 signal intensity. 6 cases from our institution followed previously reported imaging patterns.

Tipifarnib in recurrent, metastatic HRAS-mutant salivary gland cancer.

BACKGROUND: To the authors' knowledge, there are no approved therapies for recurrent, metastatic (R/M) salivary gland carcinoma (SGC), but molecularly targeted therapies warrant ongoing investigation. In the current study, the authors have reported on the efficacy of tipifarnib in patients with aggressive HRAS-mutant, R/M SGC. METHODS: The current prospective, nonrandomized, multicenter, international cohort study involved 8 centers and was conducted from May 2015 to June 2019. The median follow-up was 22 months (range, 6-55 months). Subjects with HRAS-mutant R/M SGC (any histology) and disease progression within the last 6 months were enrolled. Tipifarnib was dosed orally twice daily. The authors determined the objective response rate using Response Evaluation Criteria in Solid Tumors (version 1.1), duration of response, and molecular predictors of response. RESULTS: A total of 13 patients with R/M SGC were enrolled; all had received prior systemic therapy (1-3 regimens). One objective response was observed; an additional 7 of 12 evaluable patients (58%) had stable disease as their best response with a median duration of 9 months (range, 3-14 months). Five of 7 patients had >10% tumor regression and 6 of 7 had stable disease lasting >6 months. Q61R was the most frequent activating HRAS mutation noted (7 of 13 patients; 54%), but gene variant and allele frequency did not correlate with outcomes. The median progression-free survival was 7 months (95% confidence interval, 5.9-10.1 months), and the median overall survival was 18 months (95% confidence interval, 9.6-22.4 months) with approximately 58.6% of patients alive at 1 year. Survival was similar regardless of HRAS mutant variant or co-occurring PIK3CA alterations. No participant discontinued treatment because of toxicity. CONCLUSIONS: Tipifarnib resulted in modest clinical activity with a promising disease control rate among patients with HRAS-mutant, R/M SGC who developed disease progression within the last 6 months.

Diagnostic Yield of Staging Brain MRI in Patients with Newly Diagnosed Non-Small Cell Lung Cancer.

Background Existing guidelines are inconsistent regarding the indications for staging brain MRI in patients with newly diagnosed, early-stage non-small cell lung cancer (NSCLC). Purpose To evaluate the diagnostic yield of staging brain MRI in the initial evaluation of lung cancer. Materials and Methods This retrospective, observational, single-institution study included patients with newly diagnosed NSCLC who underwent staging chest CT and staging brain MRI from November 2017 to October 2018. Diagnostic yield was defined as the proportion of patients with brain metastases among all patients. Yield was stratified into clinical stage groups per the eighth edition of the American Joint Committee on Cancer staging guidelines, based on staging chest CT and in adenocarcinoma with epidermal growth factor receptor (EGFR) gene mutation and anaplastic lymphoma kinase (ALK) gene rearrangement. Subgroup analyses were performed on the basis of cell types and molecular markers. The χ2 test was performed to compare the diagnostic yields, and Bonferroni correction was used to account for multiple testing between stage groups. Results A total of 1712 patients (mean age, 64 years ± 10 [standard deviation]; 1035 men) were included. The diagnostic yield of staging brain MRI in newly diagnosed NSCLC was 11.9% (203 of 1712; 95% confidence interval [CI]: 10.4%, 13.5%). In clinical stage IA, IB, and II disease, the diagnostic yields were 0.3% (two of 615; 95% CI: 0.0%, 1.2%), 3.8% (seven of 186; 95% CI: 1.5%, 7.6%), and 4.7% (eight of 171; 95% CI: 2.0%, 9.0%), respectively. The diagnostic yield was higher in patients with adenocarcinoma (13.6%; 176 of 1297; 95% CI: 11.8%, 15.6%) than squamous cell carcinoma (5.9%; 21 of 354; 95% CI: 3.7%, 8.9%) and in patients with EGFR mutation-positive adenocarcinoma (17.5%; 85 of 487; 95% CI: 14.2%, 21.1%) than with EGFR mutation-negative adenocarcinoma (10.6%; 68 of 639; 95% CI: 8.4%, 13.3%) (P < .001 for both). Conclusion The diagnostic yield of staging brain MRI in clinical stage IA non-small cell lung cancer was low, but staging brain MRI had a higher diagnostic yield in clinical stage IB and epidermal growth factor receptor mutation-positive adenocarcinoma. © RSNA, 2020 Online supplemental material is available for this article.

Temporomandibular joint imaging: current clinical applications, biochemical comparison with the intervertebral disc and knee meniscus, and opportunities for advancement.

Temporomandibular disorders encompass multiple pathologies of the temporomandibular joint that manifest as middle/inner ear symptoms, headache, and/or localized TMJ symptoms. There is an important although somewhat limited role of imaging in the diagnostic evaluation of temporomandibular disorders. In this manuscript, we provide a comprehensive review of TMJ anatomy, outline potentially important features of TMJ disc ultrastructure and biochemistry in comparison with the intervertebral disc and knee meniscus, and provide imaging examples of the TMJ abnormalities currently evaluable with MRI and CT. In addition, we provide an overview of emerging and investigational TMJ imaging techniques in order to encourage further imaging research based on the biomechanical alterations of the TMJ disc.