AI assisted reader evaluation in acute CT head interpretation (AI-REACT): protocol for a multireader multicase study

Introduction A non-contrast CT head scan (NCCTH) is the most common cross-sectional imaging investigation requested in the emergency department. Advances in computer vision have led to development of several artificial intelligence (AI) tools to detect abnormalities on NCCTH. These tools are intended to provide clinical decision support for clinicians, rather than stand-alone diagnostic devices. However, validation studies mostly compare AI performance against radiologists, and there is relative paucity of evidence on the impact of AI assistance on other healthcare staff who review NCCTH in their daily clinical practice. Methods and analysis A retrospective data set of 150 NCCTH will be compiled, to include 60 control cases and 90 cases with intracranial haemorrhage, hypodensities suggestive of infarct, midline shift, mass effect or skull fracture. The intracranial haemorrhage cases will be subclassified into extradural, subdural, subarachnoid, intraparenchymal and intraventricular. 30 readers will be recruited across four National Health Service (NHS) trusts including 10 general radiologists, 15 emergency medicine clinicians and 5 CT radiographers of varying experience. Readers will interpret each scan first without, then with, the assistance of the qER EU 2.0 AI tool, with an intervening 2-week washout period. Using a panel of neuroradiologists as ground truth, the stand-alone performance of qER will be assessed, and its impact on the readers’ performance will be analysed as change in accuracy (area under the curve), median review time per scan and self-reported diagnostic confidence. Subgroup analyses will be performed by reader professional group, reader seniority, pathological finding, and neuroradiologist-rated difficulty. Ethics and dissemination The study has been approved by the UK Healthcare Research Authority (IRAS 310995, approved 13 December 2022). The use of anonymised retrospective NCCTH has been authorised by Oxford University Hospitals. The results will be presented at relevant conferences and published in a peer-reviewed journal

AI assisted reader evaluation in acute CT head interpretation (AI-REACT): protocol for a multireader multicase study.

Introduction: A non-contrast CT head scan (NCCTH) is the most common cross-sectional imaging investigation requested in the emergency department. Advances in computer vision have led to development of several artificial intelligence (AI) tools to detect abnormalities on NCCTH. These tools are intended to provide clinical decision support for clinicians, rather than stand-alone diagnostic devices. However, validation studies mostly compare AI performance against radiologists, and there is relative paucity of evidence on the impact of AI assistance on other healthcare staff who review NCCTH in their daily clinical practice. Methods and analysis: A retrospective data set of 150 NCCTH will be compiled, to include 60 control cases and 90 cases with intracranial haemorrhage, hypodensities suggestive of infarct, midline shift, mass effect or skull fracture. The intracranial haemorrhage cases will be subclassified into extradural, subdural, subarachnoid, intraparenchymal and intraventricular. 30 readers will be recruited across four National Health Service (NHS) trusts including 10 general radiologists, 15 emergency medicine clinicians and 5 CT radiographers of varying experience. Readers will interpret each scan first without, then with, the assistance of the qER EU 2.0 AI tool, with an intervening 2-week washout period. Using a panel of neuroradiologists as ground truth, the stand-alone performance of qER will be assessed, and its impact on the readers’ performance will be analysed as change in accuracy (area under the curve), median review time per scan and self-reported diagnostic confidence. Subgroup analyses will be performed by reader professional group, reader seniority, pathological finding, and neuroradiologist-rated difficulty. Ethics and dissemination: The study has been approved by the UK Healthcare Research Authority (IRAS 310995, approved 13 December 2022). The use of anonymised retrospective NCCTH has been authorised by Oxford University Hospitals. The results will be presented at relevant conferences and published in a peer-reviewed journal. Trial registration number NCT06018545

Electrical Impedance Tomography of acute stroke

Electrical Impedance Tomography (EIT) could provide a novel method for imaging in acute stroke as it could be used as an inexpensive portable imaging system, which could distinguish haemorrhage from ischaemia in acute stroke and so allow rapid deployment of thrombolysis. First, an extensive literature of the dielectrical properties of normal and pathological head tissues was undertaken to inform further studies. The recently developed UCLH Mk2 EIT system was then shown to produce reliable images in a head shaped tank and in human subjects where changing of the concentrations of a fixed volume of saline in the stomach allowed validation in-vivo with skin electrodes. This was then tested in human patients with chronic stroke, brain tumours and arteriovenous malformations as simulations of acute stroke or haemorrhage. An optimal current waveform was then found which enabled high quality imaging over the optimal band of 20Hz-500kHz with some lower frequency currents reduced to avoid painful skin stimulation. A study in a headshaped tank with improved hardware then indicated that reconstruction algorithms available were the main constraint on EIT stroke imaging. Finally, the efficacy of newly developed frequency difference algorithms was assessed in a first pilot study of patients with acute ischaemic or haemorrhagic stroke. Overall, there was no definite or statistically significant correlation between the CTs and EIT image analysis, although there were encouraging correlations in some examples. The imaging algorithm with the least errors was Weighted Frequency Difference applied to neighbouring frequency pairs. Although it was not possible to achieve the ideal goal of robust clinical imaging with EIT in human stroke subjects with scalp electrodes, this work has provided a sound foundation and specification for further studies. These are continuing in my research group in collaboration with an international medical device manufacturer

Multi-frequency electrical impedance tomography (EIT) of the adult human head: initial findings in brain tumours, arteriovenous malformations and chronic stroke, development of an analysis method and calibration

MFEIT (multi-frequency electrical impedance tomography) could distinguish between ischaemic and haemorrhagic stroke and permit the urgent use of thrombolytic drugs in patients with ischaemic stroke. The purpose of this study was to characterize the UCLH Mk 2 MFEIT system, designed for this purpose, with 32 electrodes and a multiplexed 2 kHz to 1.6 MHz single impedance measuring circuit. Data were collected in seven subjects with brain tumours, arteriovenous malformations or chronic stroke, as these resembled the changes in haemorrhagic or ischaemic stroke. Calibration studies indicated that the reliable bandwidth was only 16–64 kHz because of front-end components placed to permit simultaneous EEG recording. In raw in-phase component data, the SD of 16–64 kHz data for one electrode combination across subjects was 2.45 ± 0.9%, compared to a largest predicted change of 0.35% estimated using the FEM of the head. Using newly developed methods of examining the most sensitive channels from the FEM, and nonlinear imaging constrained to the known site of the lesion, no reproducible changes between pathologies were observed. This study has identified a specification for accuracy in EITS in acute stroke, identified the size of variability in relation to this in human recordings, and presents new methods for analysis of data. Although no reproducible changes were identified, we hope this will provide a foundation for future studies in this demanding but potentially powerful novel application

Design and calibration of a compact multi-frequency EIT system for acute stroke imaging

A new, compact UCLH Mk 2.5 EIT system has been developed and calibrated for EIT imaging of the head. Improvements include increased input and output impedances, increased bandwidth and improved CMRR (80 dB) and linearity over frequencies and load (0.2% on a single channel, ±0.7% on a saline tank over 20 Hz–256 kHz and 10–65 Ω). The accuracy of the system is sufficient to image severe acute stroke according to the specification from recent detailed anatomical modelling (Horesh et al 2005 3rd European Medical and Biological Engineering Conference EMBEC'05). A preliminary human study has validated the main specifications of the modelling, the range of trans-impedance from the head (8–70 Ω) using a 32 electrode, 258 combination protocol and contact impedances of 300 Ω to 2.7 kΩ over 20 Hz to 256 kHz