RadioGraphics Update: Parathyroid CT and Primary Hyperparathyroidism.

Editor's Note.-RadioGraphics Update articles supplement or update information found in full-length articles previously published in RadioGraphics. These updates, written by at least one author of the previous article, provide a brief synopsis that emphasizes important new information such as technological advances, revised imaging protocols, new clinical guidelines involving imaging, or updated classification schemes.

Screening for extranodal extension in HPV-associated oropharyngeal carcinoma: evaluation of a CT-based deep learning algorithm in patient data from a multicentre, randomised de-escalation trial.

BACKGROUND: Pretreatment identification of pathological extranodal extension (ENE) would guide therapy de-escalation strategies for in human papillomavirus (HPV)-associated oropharyngeal carcinoma but is diagnostically challenging. ECOG-ACRIN Cancer Research Group E3311 was a multicentre trial wherein patients with HPV-associated oropharyngeal carcinoma were treated surgically and assigned to a pathological risk-based adjuvant strategy of observation, radiation, or concurrent chemoradiation. Despite protocol exclusion of patients with overt radiographic ENE, more than 30% had pathological ENE and required postoperative chemoradiation. We aimed to evaluate a CT-based deep learning algorithm for prediction of ENE in E3311, a diagnostically challenging cohort wherein algorithm use would be impactful in guiding decision-making. METHODS: For this retrospective evaluation of deep learning algorithm performance, we obtained pretreatment CTs and corresponding surgical pathology reports from the multicentre, randomised de-escalation trial E3311. All enrolled patients on E3311 required pretreatment and diagnostic head and neck imaging; patients with radiographically overt ENE were excluded per study protocol. The lymph node with largest short-axis diameter and up to two additional nodes were segmented on each scan and annotated for ENE per pathology reports. Deep learning algorithm performance for ENE prediction was compared with four board-certified head and neck radiologists. The primary endpoint was the area under the curve (AUC) of the receiver operating characteristic. FINDINGS: From 178 collected scans, 313 nodes were annotated: 71 (23%) with ENE in general, 39 (13%) with ENE larger than 1 mm ENE. The deep learning algorithm AUC for ENE classification was 0·86 (95% CI 0·82-0·90), outperforming all readers (p<0·0001 for each). Among radiologists, there was high variability in specificity (43-86%) and sensitivity (45-96%) with poor inter-reader agreement (κ 0·32). Matching the algorithm specificity to that of the reader with highest AUC (R2, false positive rate 22%) yielded improved sensitivity to 75% (+ 13%). Setting the algorithm false positive rate to 30% yielded 90% sensitivity. The algorithm showed improved performance compared with radiologists for ENE larger than 1 mm (p<0·0001) and in nodes with short-axis diameter 1 cm or larger. INTERPRETATION: The deep learning algorithm outperformed experts in predicting pathological ENE on a challenging cohort of patients with HPV-associated oropharyngeal carcinoma from a randomised clinical trial. Deep learning algorithms should be evaluated prospectively as a treatment selection tool. FUNDING: ECOG-ACRIN Cancer Research Group and the National Cancer Institute of the US National Institutes of Health.

Incorporating algorithmic uncertainty into a clinical machine deep learning algorithm for urgent head CTs.

Machine learning (ML) algorithms to detect critical findings on head CTs may expedite patient management. Most ML algorithms for diagnostic imaging analysis utilize dichotomous classifications to determine whether a specific abnormality is present. However, imaging findings may be indeterminate, and algorithmic inferences may have substantial uncertainty. We incorporated awareness of uncertainty into an ML algorithm that detects intracranial hemorrhage or other urgent intracranial abnormalities and evaluated prospectively identified, 1000 consecutive noncontrast head CTs assigned to Emergency Department Neuroradiology for interpretation. The algorithm classified the scans into high (IC+) and low (IC-) probabilities for intracranial hemorrhage or other urgent abnormalities. All other cases were designated as No Prediction (NP) by the algorithm. The positive predictive value for IC+ cases (N = 103) was 0.91 (CI: 0.84-0.96), and the negative predictive value for IC- cases (N = 729) was 0.94 (0.91-0.96). Admission, neurosurgical intervention, and 30-day mortality rates for IC+ was 75% (63-84), 35% (24-47), and 10% (4-20), compared to 43% (40-47), 4% (3-6), and 3% (2-5) for IC-. There were 168 NP cases, of which 32% had intracranial hemorrhage or other urgent abnormalities, 31% had artifacts and postoperative changes, and 29% had no abnormalities. An ML algorithm incorporating uncertainty classified most head CTs into clinically relevant groups with high predictive values and may help accelerate the management of patients with intracranial hemorrhage or other urgent intracranial abnormalities.

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.

Late Radiation-Induced Carotid Artery Stenosis and Stroke in Pediatric Patient Treated With Proton Radiation Therapy for Skull-Base Chordoma.

Radiation vasculopathy is a well-recognized late complication of radiation therapy. We present a case of a stroke 29 years after high-dose proton radiation therapy for skull-base chordoma due to occlusion of bilateral internal carotid arteries.

Magnetic Resonance Imaging of Head and Neck Emergencies, a Symptom-Based Review, Part 1: General Considerations, Vision Loss, and Eye Pain.

Use of magnetic resonance (MR) imaging in the emergency department continues to increase. Although computed tomography is the first-line imaging modality for most head and neck emergencies, MR is superior in some situations and imparts no ionizing radiation. This article provides a symptom-based approach to nontraumatic head and neck pathologic conditions most relevant to emergency head and neck MR imaging, emphasizing relevant anatomy, "do not miss" findings affecting clinical management, and features that may aid differentiation from potential mimics. Essential MR sequences and strategies for obtaining high-quality images when faced with patient motion and other technical challenges are also discussed.

Magnetic Resonance Imaging of Head and Neck Emergencies, a Symptom-Based Review, Part 2: Ear Pain, Face Pain, and Fever.

The use of magnetic resonance (MR) imaging in the emergency department continues to increase. Although computed tomography is the first-line imaging modality for most head and neck emergencies, MR is superior in some situations and imparts no ionizing radiation. This article provides a symptom-based approach to nontraumatic head and neck pathologic conditions most relevant to emergency head and neck MR imaging, emphasizing relevant anatomy, "do not miss" findings affecting clinical management, and features that may aid differentiation from potential mimics. Essential MR sequences and strategies for obtaining high-quality images when faced with patient motion and other technical challenges are also discussed.

Parathyroid Computed Tomography: Pearls, Pitfalls, and Our Approach.

Parathyroid imaging is predominantly used for preoperative localization of parathyroid lesions in patients with the biochemical diagnosis of primary hyperparathyroidism. Although imaging algorithms vary, in the era of minimally invasive parathyroidectomy for single parathyroid adenomas, multiphase parathyroid computed tomography (CT) (4-dimensional CT) has emerged as a favored modality for presurgical mapping of parathyroid lesions. Implementation and correct interpretation of these studies can be challenging, although confidence and accuracy improve with experience and volume. This article reviews our approach to parathyroid imaging, focusing on pearls and pitfalls in parathyroid CT with ultrasound as a supportive and complementary modality.

Biosimilar Pegfilgrastim-cbqv Demonstrated Similar Immunogenicity to Pegfilgrastim in Healthy Subjects Across Three Randomized Clinical Studies.

INTRODUCTION: Biologic therapeutics can trigger immune responses in patients. As part of the totality of evidence that is required for regulatory approval of biosimilars, immunogenicity similarity must be assessed in the clinical programs. Pegfilgrastim-cbqv (UDENYCA®) is a pegfilgrastim biosimilar approved in the USA and European Union. This article demonstrates the similar immunogenicity of pegfilgrastim-cbqv compared with its reference product, pegfilgrastim (Neulasta®). METHODS: The immunogenicity of pegfilgrastim-cbqv was assessed in three clinical studies in healthy subjects (one specifically designed to evaluate immunogenicity similarity and two studies to assess pharmacokinetics and pharmacodynamics bioequivalence) using a tiered approach, in which plasma samples were tested for the presence of antidrug antibodies (ADAs) as well as ADA binding-specificity, titer and neutralizing activity. To assess the clinical impact of ADAs, pharmacokinetics, pharmacodynamics and safety profiles were compared between ADA-positive and -negative subjects. RESULTS: These studies demonstrated similar immunogenicity of pegfilgrastim-cbqv and pegfilgrastim. The small differences in ADA incidence between treatment groups observed in the immunogenicity study were driven by non-neutralizing, low-titer, polyethylene glycol (PEG)-reactive ADAs, which are commonly present in healthy subjects. No treatment-emergent neutralizing antibodies (NAbs) were detected in either treatment group, and there was no apparent impact of ADAs on pharmacokinetics, pharmacodynamics or safety. CONCLUSION: Pegfilgrastim-cbqv has similar immunogenicity to pegfilgrastim. The presented immunogenicity, pharmacokinetics, pharmacodynamics and safety data support the overall demonstration of no clinically meaningful differences between pegfilgrastim-cbqv and pegfilgrastim. CLINICAL TRIAL REGISTRATION: NCT02418104 (CHS-1701-04, April 2015), NCT02650973 (CHS-1701-05, February 2016) and NCT02385851 (CHS-1701-03, March 2015).

Factors Influential in the Selection of Radiology Residents in the Post-Step 1 World: A Discrete Choice Experiment.

OBJECTIVES: Reporting of United States Medical Licensing Examination Step 1 results will transition from a numerical score to a pass or fail result. We sought an objective analysis to determine changes in the relative importance of resident application attributes when numerical Step 1 results are replaced. METHODS: A discrete choice experiment was designed to model radiology resident selection and determine the relative weights of various application factors when paired with a numerical or pass or fail Step 1 result. Faculty involved in resident selection at 14 US radiology programs chose between hypothetical pairs of applicant profiles between August and November 2020. A conditional logistic regression model assessed the relative weights of the attributes, and odds ratios (ORs) were calculated. RESULTS: There were 212 participants. When a numerical Step 1 score was provided, the most influential attributes were medical school (OR: 2.35, 95% confidence interval [CI]: 2.07-2.67), Black or Hispanic race or ethnicity (OR: 2.04, 95% CI: 1.79-2.38), and Step 1 score (OR: 1.8, 95% CI: 1.69-1.95). When Step 1 was reported as pass, the applicant's medical school grew in influence (OR: 2.78, 95% CI: 2.42-3.18), and there was a significant increase in influence of Step 2 scores (OR: 1.31, 95% CI: 1.23-1.40 versus OR 1.57, 95% CI: 1.46-1.69). There was little change in the relative influence of race or ethnicity, gender, class rank, or clerkship honors. DISCUSSION: When Step 1 reporting transitions to pass or fail, medical school prestige gains outsized influence and Step 2 scores partly fill the gap left by Step 1 examination as a single metric of decisive importance in application decisions.

Utilization of a Virtual Information Session to Increase Engagement With Prospective Applicants in the Setting of COVID-19.

PURPOSE: This study aimed to assess the efficacy of a virtual information session hosted by a diagnostic radiology residency program at addressing applicant concerns about the 2020-2021 interview cycle and highlighting key aspects of the residency program. METHODS: Participants were recruited to attend the virtual information session over a 2-week period via social media and communication with medical school radiology interest groups. Attendees were able to submit questions or topics of interest prior to the session. The virtual information session was hosted by trainees and faculty from a radiology residency. Data regarding the demographics of the attendees and the efficacy of the session were obtained through interactive live polling during the virtual session and a voluntary anonymous postsession survey. RESULTS: A total of 171 attendees participated in the virtual information session. Of the attendees, 42% learned about the session from Twitter and 72% were fourth-year medical students applying for residency. Among topics addressed during the session, attendees indicated that they were most interested in learning about "Application strategies during COVID-19" during an in-session poll. On the post-session survey, 96% of attendees reported being more knowledgeable about the residency program culture and the breadth of research and educational opportunities. CONCLUSION: Given the virtual nature of the 2020-2021 residency application cycle, utilization of web-based platforms for recruitment will be essential. Virtual information sessions can be effective at providing insight into aspects of a residency program that are typically gained during the in-person interview experience.

Pharmacokinetic and Pharmacodynamic Equivalence of Pegfilgrastim-cbqv and Pegfilgrastim in Healthy Subjects.

INTRODUCTION: Pegfilgrastim-cbqv was developed as a biosimilar of pegfilgrastim, a pegylated form of recombinant human granulocyte colony-stimulating factor approved for decreasing febrile neutropenia-associated infection in patients receiving myelosuppressive drugs. This multicenter, randomized, single-blind, partial-reference-replicated, three-sequence crossover study assessed pharmacokinetic and pharmacodynamic bioequivalence of pegfilgrastim-cbqv and pegfilgrastim in healthy subjects. METHODS: One hundred twenty-two subjects were randomized to one of three treatment sequences; each included one dose of pegfilgrastim-cbqv and two doses of pegfilgrastim separated by ≥ 28 days. The primary pharmacokinetic end points were area under the curve (AUC) from 0 to infinity (AUC0-∞) and maximum concentration (Cmax). The primary pharmacodynamic end points were maximum absolute neutrophil count (ANCmax) and ANC AUC from time 0 to the last measurable observation (ANC AUC0-last). Pharmacokinetic and pharmacodynamic bioequivalences were demonstrated if the 90% CI for the geometric mean ratio (GMR) of pegfilgrastim-cbqv to pegfilgrastim was within 80-125% for the primary end points. RESULTS: Pharmacokinetic bioequivalence criteria were met for Cmax (GMR 105.0; 90% CI 95.5-115.4) and AUC0-∞ (GMR 97.5; 90% CI 88.6-107.2). Pharmacodynamic bioequivalence criteria were met for ANCmax (GMR 99.6; 90% CI 96.2-103.2) and ANC AUC0-last (GMR 96.7; 90% CI 92.2-101.4). Adverse events occurred in 76.0%, 76.6%, and 73.1% of subjects for pegfilgrastim-cbqv, first pegfilgrastim, and second pegfilgrastim dosing periods across treatment sequences, respectively. Investigators found no drug-related serious adverse events. CONCLUSION: This study established pharmacokinetic and pharmacodynamic bioequivalence of pegfilgrastim-cbqv to pegfilgrastim. The treatments displayed similar safety profiles, including immunogenicity, with no unexpected safety findings. CLINICAL TRIALS REGISTRATION: ClinicalTrials.gov, NCT02650973, February 2016.

Parathyroid 4D CT: What the Surgeon Wants to Know.

Parathyroid four-dimensional (4D) CT is an increasingly used and powerful tool for preoperative localization of abnormal parathyroid tissue in the setting of primary hyperparathyroidism. Accurate and precise localization of a single adenoma facilitates minimally invasive parathyroidectomy, and localization of multiglandular disease aids bilateral neck exploration. However, many radiologists find the interpretation of these examinations to be an intimidating challenge. The authors review parathyroid 4D CT findings of typical and atypical parathyroid lesions and provide illustrative examples. Relevant anatomy, embryology, and operative considerations with which the radiologist should be familiar to provide clinically useful image interpretations are also discussed. The most important 4D CT information to the surgeon includes the number, size, and specific location of candidate parathyroid lesions with respect to relevant surgical landmarks; the radiologist's opinion and confidence level regarding what each candidate lesion represents; and the presence or absence of ectopic or supernumerary parathyroid tissue, concurrent thyroid pathologic conditions, and arterial anomalies associated with a nonrecurrent laryngeal nerve. The authors provide the radiologist with an accessible and practical approach to performing and interpreting parathyroid 4D CT images, detail what the surgeon really wants to know from the radiologist and why, and provide an accompanying structured report outlining the key information to be addressed. By accurately reporting and concisely addressing the key information the surgeon desires from a parathyroid 4D CT examination, the radiologist substantially impacts patient care by enabling the surgeon to develop and execute the best possible operative plan for each patient. ©RSNA, 2020.

Chew on This: Emergency Imaging of the Oral Cavity and Salivary Glands-What the Clinician Really Needs to Know.

Nontraumatic emergencies of the oral cavity, sublingual and submandibular spaces, and salivary glands are common and those requiring imaging will most often be infectious in nature.1,2 However, noninfectious pathologies such as sialolithiasis, autoimmune sialoadenitis, and soft tissue swelling due to angioedema or hemorrhage are also important conditions that radiologists must be familiar with in order to inform the clinician of critical imaging findings that can have a profound impact on patient outcomes. To understand these pathologies, familiarity with the anatomy of these spaces is essential.