Pearls and pitfalls in emergency CT neuroangiography through the lens of bias and error.

Computed tomography angiography (CTA) of the head and neck is central in emergency department (ED) evaluation of clinically suspected acute stroke and intracranial hemorrhage. Timely and accurate detection of acute findings is crucial for best clinical outcomes; missed or delayed diagnosis can be devastating. Our pictorial essay presents twelve CTA cases that provided significant diagnostic dilemmas to on-call trainees while reviewing current bias and error classifications in radiology. Among others, we discuss anchoring, automation, framing, satisfaction of search, scout neglect and zebra-retreat bias. Each imaging vignette depicts a potential diagnostic "pitfall" while introducing types of cognitive bias/error before concluding with a concrete "pearl" for CTA interpretation. We believe that familiarity with bias and error is particularly important in the ED setting where high case volume, high acuity and radiologist fatigue intersect. Particular attention to personal cognitive biases and these potential CTA pitfalls may help emergency radiologists transition from habit-driven pattern recognition to analytical thinking, ultimately improving diagnostic decision making.

A Systematic Review of the Existing Prostate Imaging Reporting and Data System Version 2 (PI-RADSv2) Literature and Subset Meta-Analysis of PI-RADSv2 Categories Stratified by Gleason Scores.

OBJECTIVE: The objective of this study was to quantitatively and qualitatively assess the methodologic heterogeneity of the current Prostate Imaging Reporting and Data System version 2 (PI-RADSv2) literature and estimate the proportions of Gleason scores (GSs) diagnosed across PI-RADSv2 categories. MATERIALS AND METHODS: This study was a systematic review and meta-analysis and was performed in concordance with the Preferred Reporting Items for Systematic Reviews and Meta-Analyses (PRISMA) guidelines. Only English-language studies and studies published before April 1, 2018, were assessed. The primary outcome of the meta-analysis was the estimated percentage of patients with GS ≥ 3 + 4 within each individual PI-RADSv2 score. We calculated the pooled estimates and 95% CIs on the basis of a random-effects model using the meta-analysis routine of Stata (version 13.1). RESULTS: Our search revealed 434 titles, and 59 of these studies were selected. These studies were remarkable for their technical and terminological diverseness. Thirteen studies had sufficient data to be included in the meta-analysis. The prevalence of ≥ GS 3 + 4 in lesions assigned a PI-RADSv2 score of 3 or higher was approximately 45%. Lesions assigned PI-RADSv2 scores 1 or 2, 3, 4, and 5 represented high-grade disease in approximately 6%, 12%, 48%, and 72% of patients. CONCLUSION: The data available in the literature are highly heterogeneous and challenging to analyze because of variations in terminology, patient cohort selection, criteria, imaging parameters, and reference standards. In spite of this heterogeneity, our meta-analysis shows that PI-RADSv2 has good sensitivity when a score of ≥ 3 is considered as a positive test.

The effect of scan and patient parameters on the diagnostic performance of AI for detecting coronary stenosis on coronary CT angiography.

OBJECTIVES: To determine whether coronary computed tomography angiography (CCTA) scanning, scan preparation, contrast, and patient based parameters influence the diagnostic performance of an artificial intelligence (AI) based analysis software for identifying coronary lesions with ≥50% stenosis. BACKGROUND: CCTA is a noninvasive imaging modality that provides diagnostic and prognostic benefit to patients with coronary artery disease (CAD). The use of AI enabled quantitative CCTA (AI-QCT) analysis software enhances our diagnostic and prognostic ability, however, it is currently unclear whether software performance is influenced by CCTA scanning parameters. METHODS: CCTA and quantitative coronary CT (QCT) data from 303 stable patients (64 ± 10 years, 71% male) from the derivation arm of the CREDENCE Trial were retrospectively analyzed using an FDA-cleared cloud-based software that performs AI-enabled coronary segmentation, lumen and vessel wall determination, plaque quantification and characterization, and stenosis determination. The algorithm's diagnostic performance measures (sensitivity, specificity, and accuracy) for detecting coronary lesions of ≥50% stenosis were determined based on concordance with QCA measurements and subsequently compared across scanning parameters (including scanner vendor, model, single vs dual source, tube voltage, dose length product, gating technique, timing method), scan preparation technique (use of beta blocker, use and dose of nitroglycerin), contrast administration parameters (contrast type, infusion rate, iodine concentration, contrast volume) and patient parameters (heart rate and BMI). RESULTS: Within the patient cohort, 13% demonstrated ≥50% stenosis in 3 vessel territories, 21% in 2 vessel territories, 35% in 1 vessel territory while 32% had <50% stenosis in all vessel territories evaluated by QCA. Average AI analysis time was 10.3 ± 2.7 min. On a per vessel basis, there were significant differences only in sensitivity for ≥50% stenosis based on contrast type (iso-osmolar 70.0% vs non isoosmolar 92.1% p = 0.0345) and iodine concentration (<350 mg/ml 70.0%, 350-369 mg/ml 90.0%, 370-400 mg/ml 90.0%, >400 mg/ml 95.2%; p = 0.0287) in the context of low injection flow rates. On a per patient basis there were no significant differences in AI diagnostic performance measures across all measured scanner, scan technique, patient preparation, contrast, and individual patient parameters. CONCLUSION: The diagnostic performance of AI-QCT analysis software for detecting moderate to high grade stenosis are unaffected by commonly used CCTA scanning parameters and across a range of common scanning, scanner, contrast and patient variables. CONDENSED ABSTRACT: An AI-enabled quantitative CCTA (AI-QCT) analysis software has been validated as an effective tool for the identification, quantification and characterization of coronary plaque and stenosis through comparison to blinded expert readers and quantitative coronary angiography. However, it is unclear whether CCTA screening parameters related to scanner parameters, scan technique, contrast volume and rate, radiation dose, or a patient's BMI or heart rate at time of scan affect the software's diagnostic measures for detection of moderate to high grade stenosis. AI performance measures were unaffected across a broad range of commonly encountered scanner, patient preparation, scan technique, intravenous contrast and patient parameters.

Pyriform sinus rupture caused by blunt trauma.

Hypopharyngeal perforation (HP) is a potentially life-threatening condition most associated with iatrogenic injury and foreign body impaction. Additionally, a number of cases of posterior HP have been reported following blunt cervical trauma. We present a case of a construction accident causing lateral hypopharyngeal rupture. Visceral perforation was initially diagnosed on computed tomography (CT) imaging and managed conservatively. We speculate this region may be particularly vulnerable to injury due to an anatomic transition in adjacent fascial support. A review of 29 prior cases suggests that this may be the first reported case of blunt trauma causing rupture of the pyriform sinus. However, significant heterogeneity exists in diagnostic approach. Radiography and CT are rapid, sensitive modalities for suggesting pharyngeal perforation, while fluoroscopy and endoscopy can better assess injury size and location and monitor resolution. Early radiologic recognition of hypopharyngeal injury is essential to initiate appropriate treatment. In certain cases, including our own, both the presence and specific location of perforation may be identified on initial CT images.

Ferromagnetic sand: A possible MRI hazard.

While the ferromagnetic properties of metallic objects, implantable medical devices, and cosmetics are well known, sand is not generally considered a consequential substance. Beaches in specific geographic regions, including the San Francisco Bay Area, have a propensity for ferromagnetic sand because of their geologic history. We describe a case in which ferromagnetic sand in a patient's hair coated the magnetic resonance imaging (MRI) scanner bore and caused significant imaging artifact, fortunately with no harm to the patient. We recommend that MRI facilities in areas where ferromagnetic sand is found consider educating technologists and screening patients for recent black sand exposure prior to scanning.

Neuroimaging findings in Pallister-Killian syndrome.

Pallister-Killian syndrome (PKS) is a rare chromosomal duplication disorder caused by additional copies of the short arm of chromosome 12 (12p). Clinically PKS is characterized by craniofacial dysmorphism with neonatal frontotemporal alopecia, hypertelorism, and low-set ears as well as kyphoscoliosis, severe intellectual disability, epilepsy, and abnormal muscle tone. Comprehensive high-resolution brain MR findings of PKS in childhood have not been previously illustrated in the medical literature. We present detailed neuroimaging findings from a child with PKS and thoroughly review previously reported structural brain abnormalities in this patient population. MRI abnormalities common to PKS include cerebral volume loss, malformations of cortical development, corpus callosum dysgenesis, white matter disease, and craniofacial malformations. In our patient, new findings of perisylvian with occipital polymicrogyria, vermian dysplasia, brachium pontis signal abnormality, dural anomalies, and unilateral atlas assimilation were noted. Micrencephaly and cortical dysplasia provide a likely explanation for severe intellectual disability and epilepsy in this patient population.