Emergency CT misdiagnosis in acute aortic syndrome

Objectives: This cross-sectional study assessed the accuracy of emergency CT reports at presentation in acute aortic syndrome (AAS). Methods: Retrospective identification of cases of AAS presenting within a large health board with three acute hospitals receiving adult patients between January 2013 and December 2016. CT studies and reports at presentation were reviewed for discrepancies related to diagnosis, complications and classification by two cardiovascular radiologists. The specialist interest of the original reporters, clinically suspected diagnosis at referral for CT and technical adequacy of the scans were also assessed. False-positive diagnoses were identified and evaluated separately. Results: Among 88 consecutive confirmed cases of AAS at least one discrepancy was identified in 31% (n = 27), including failure to identify or misinterpretation of the AAS itself in 15% (n = 13), haemorrhage in 13% (n = 11), branch involvement in 9% (n = 8), and misclassification in 3% (n = 3). All discrepancies occurred among the 80% (n = 70) of cases reported by radiologists without specialist cardiovascular interest. 26% (n = 23/88) of AAS cases were not clinically suspected at referral for CT and although this was associated with suboptimal protocols, only 51% of CT scans among suspected cases were technically adequate. Seven false-positive diagnoses were identified, three of which related to motion artefact. Conclusion: Significant discrepancies are common in the emergency CT assessment of positive cases AAS and this study highlights important pitfalls in CT technique and interpretation. The absence of discrepancies among radiologists with specialist cardiovascular interest suggests both suspected and confirmed cases warrant urgent specialist review. Advances in knowledge: CT angiography is central to the diagnosis of AAS; however, significant radiology discrepancies are common among non-specialists. This study highlights important pitfalls in both CT technique as well as interpretation and supports routine specialist cardiovascular imaging input in the emergency assessment of AAS.

Minimizing table time in patients with claustrophobia using focused ferumoxytol-enhanced MR angiography (f-FEMRA): a feasibility study

Objectives: To assess the feasibility of a rapid, focused ferumoxytol-enhanced MR angiography (f-FEMRA) protocol in patients with claustrophobia. Methods: In this retrospective study, 13 patients with claustrophobia expressed reluctance to undergo conventional MR angiography, but agreed to a trial of up to 10 min in the scanner bore and underwent f-FEMRA. Thirteen matched control patients who underwent gadolinium-enhanced MR angiography (GEMRA) were identified for comparison of diagnostic image quality. For f-FEMRA, the time from localizer image acquisition to completion of the angiographic acquisition was measured. Two radiologists independently scored images on both f-FEMRA and GEMRA for arterial and venous image quality, motion artefact and diagnostic confidence using a 5-point scale, five being best. Signal-to-noise ratio (SNR) and contrast-to-noise ratio (CNR) in the aorta and IVC were measured. The Wilcoxon rank-sum test, one-way ANOVA with Tukey correction and two-tailed t tests were utilized for statistical analyses. Results: All scans were diagnostic and assessed with high confidence (scores ≥ 4). Average scan time for f-FEMRA was 6.27 min (range 3.56 to 10.12 min), with no significant difference between f-FEMRA and GEMRA in diagnostic confidence (4.86 ± 0.24 vs 4.69 ± 0.25, p = 0.13), arterial image quality (4.62 ± 0.57 vs 4.65 ± 0.49, p = 0.78) and motion artefact score (4.58 ± 0.49 vs 4.58 ± 0.28, p > 0.99). f-FEMRA scored significantly better for venous image quality than GEMRA (4.62 ± 0.42 vs 4.19 ± 0.56, p = 0.04). CNR in the IVC was significantly higher for steady-state f-FEMRA than GEMRA regardless of the enhancement phase (p < 0.05). Conclusions: Comprehensive vascular MR imaging of the thorax, abdomen and pelvis can be completed in as little as 5 min within the magnet bore using f-FEMRA, facilitating acceptance by patients with claustrophobia and streamlining workflow. Advances in knowledge: A focused approach to vascular imaging with ferumoxytol can be performed in patients with claustrophobia, limiting time in the magnet bore to 10 min or less, while acquiring fully diagnostic images of the thorax, abdomen and pelvis.

T2-PROPELLER Compared to T2-FRFSE for Image Quality and Lesion Detection at Prostate MRI

Purpose: The primary objective was to compare T2-FRFSE and T2-PROPELLER sequences for image quality. The secondary objective was to compare the ability to detect prostate lesions at MRI in the presence and absence of motion artefact using the 2 sequences. Methods: 99 patients underwent 3 T MRI examination of the prostate, including T2-FRFSE and T2-PROPELLER sequences. All patients underwent prostate biopsy. Two independent readers rated overall image quality, presence of motion artefact, and blurring for both sequences using a 5-point Likert scale. Scores were compared for the whole group and for subgroups with and without significant motion artefact. Outcome for lesion detection at an MRI threshold of PI-RADS score ≥3 was compared between T2-FRFSE and T2-PROPELLER. Results: The overall image quality was not significantly different between T2-FRFSE and T2-PROPELLER sequences (3.74 vs. 3.93, p = 0.275). T2-PROPELLER recorded a lesser degree of motion artefact (score 4.53 vs. 3.78, p <0.0001), but demonstrated greater image blurring (score 3.29 vs. 3.73, p <0.001). However, in a subgroup of patients with significant motion artefact on T2-FRFSE, the T2-PROPELLER sequence demonstrated significantly higher image quality (3.46 vs. 2.49, p <0.001). T2-FRFSE and T2-PROPELLER showed comparable positive predictive values for lesion detection at 93.2% and 97.7%, respectively. Conclusions: T2-PROPELLER provides higher quality imaging in the presence of motion artefact, but T2-FRFSE is preferred in the absence of motion. T2-PROPELLER is therefore recommended as a secondary T2 sequence when imaging requires repeat acquisition due to motion artefact.

Motion artefact removal in electroencephalography and electrocardiography by using multichannel inertial measurement units and adaptive filtering

This paper presents a new active electrode design for electroencephalogram (EEG) and electrocardiogram (ECG) sensors based on inertial measurement units to remove motion artefacts during signal acquisition. Rather than measuring motion data from a single source for the entire recording unit, inertial measurement units are attached to each individual EEG or ECG electrode to collect local movement data. This data is then used to remove the motion artefact by using normalised least mean square adaptive filtering. Results show that the proposed active electrode design can reduce motion contamination from EEG and ECG signals in chest movement and head swinging motion scenarios. However, it is found that the performance varies, necessitating the need for the algorithm to be paired with more sophisticated signal processing to identify scenarios where it is beneficial in terms of improving signal quality. The new instrumentation hardware allows data driven artefact removal to be performed, providing a new data driven approach compared to widely used blind-source separation methods, and helps enable in the wild EEG recordings to be performed.

Motion artefact removal in electroencephalography and electrocardiography by using multichannel inertial measurement units and adaptive filtering

This paper presents a new active electrode design for electroencephalogram (EEG) and electrocardiogram (ECG) sensors based on Inertial Measurement Units (IMUs) to remove motion artefacts during signal acquisition. Rather than measuring motion data from a single source for the entire recording unit, IMUs are attached to each individual EEG or ECG electrode to collect more local movement data. This movement data is then used to remove the motion artefact by using Normalised Least Mean Square (NLMS) adaptive filtering. Results show that the proposed active electrode design can reduce motion contamination from EEG and ECG signals in chest movement and head swinging motion scenarios. However the performance depends on the quality of the input signal with the algorithm providing better performance on signals with lower signal-to-noise ratios. The new instrumentation hardware allows data driven artefact removal to be performed, providing a new approach compared to widely used, non-parametric, blind-source separation methods, and helps enable \emph{in the wild} EEG recordings to be performed.

Motion artefact removal in electroencephalography and electrocardiography by using multichannel inertial measurement units and adaptive filtering

This paper presents a new active electrode design for electroencephalogram (EEG) and electrocardiogram (ECG) sensors based on Inertial Measurement Units (IMUs) to remove motion artefacts during signal acquisition. Rather than measuring motion data from a single source for the entire recording unit, IMUs are attached to each individual EEG or ECG electrode to collect more local movement data. This movement data is then used to remove the motion artefact by using Normalised Least Mean Square (NLMS) adaptive filtering. Results show that the proposed active electrode design can reduce motion contamination from EEG and ECG signals in chest movement and head swinging motion scenarios. However the performance depends on the quality of the input signal with the algorithm providing better performance on signals with lower signal-to-noise ratios. The new instrumentation hardware allows data driven artefact removal to be performed, providing a new approach compared to widely used, non-parametric, blind-source separation methods, and helps enable \emph{in the wild} EEG recordings to be performed.