Background and purpose Brainomix e-Stroke is an artificial intelligence-based decision support tool that aids the interpretation of CT imaging in the context of acute stroke. While e-Stroke has the potential to improve the speed and accuracy of diagnosis, real-world validation is essential. The aim of this study was to prospectively evaluate the performance of Brainomix e-Stroke in an unselected cohort of patients with suspected acute ischaemic stroke. Methods The study cohort included all patients admitted to the University College London Hospital Hyperacute Stroke Unit between October 2021 and April 2022. For e-ASPECTS and e-CTA, the ground truth was determined by a neuroradiologist with access to all clinical and imaging data. For e-CTP, the values of the core infarct and ischaemic penumbra were compared with those derived from syngo.via, an alternate software used at our institution. Results 1163 studies were performed in 551 patients admitted during the study period. Of these, 1130 (97.2%) were successfully processed by e-Stroke in an average of 4 min. For identifying acute middle cerebral artery territory ischaemia, e-ASPECTS had an accuracy of 77.0% and was more specific (83.5%) than sensitive (58.6%). The accuracy for identifying hyperdense thrombus was lower (69.1%), which was mainly due to many false positives (positive predictive value of 22.9%). Identification of acute haemorrhage was highly accurate (97.8%) with a sensitivity of 100% and a specificity of 97.6%; false positives were typically caused by areas of calcification. The accuracy of e-CTA for large vessel occlusions was 91.5%. The core infarct and ischaemic penumbra volumes provided by e-CTP strongly correlated with those provided by syngo.via (ρ=0.804—0.979). Conclusion Brainomix e-Stroke software provides rapid and reliable analysis of CT imaging in the acute stroke setting although, in line with the manufacturer’s guidance, it should be used as an adjunct to expert interpretation rather than a standalone decision-making tool.

Background: The increasing detection of non-palpable breast lesions necessitates accurate preoperative localization to ensure complete excision while preserving healthy tissue and optimizing cosmetic outcomes. Traditional wire-guided localization (WL) has been the gold standard; however, it has several drawbacks, including patient discomfort and scheduling challenges. This study evaluates the accuracy and feasibility of radiofrequency identification (RFID) tag localization using the Hologic LOCalizer™ system as an alternative technique. Methods: This retrospective study included 258 consecutive patients who underwent image-guided RFID tag localization from March 2021 to February 2023 from a single-center London breast unit. The primary outcome measured was the accuracy of RFID tag placement, defined as within 10 mm of the target lesion on post-clip mammograms. Secondary outcomes included type and size of lesions, re-excision rates, review of post-operative specimen radiographs, and patient demographics. Results: A total of 297 RFID tags were placed, with 95.6% accurately positioned within the target range. The median target size was 29 mm, with the most common abnormalities being mass lesions (64%). Among the 13 inaccurately placed RFID tags (4.4%), all were identified preoperatively, with two requiring additional wire placements. RFID tags were successfully identified in 92% of specimen radiographs, and 8% of patients required re-excision due to positive or close margins. Notably, patients with multiple RFID tags showed a higher incidence of re-excision. Conclusions: The LOCalizer™ RFID system demonstrated a high accuracy rate for preoperative localization of breast lesions, presenting a viable alternative to WL. This technique improves surgical scheduling flexibility and enhances patient comfort. Comparative studies with other wire-free localization technologies, such as magnetic seeds and radar reflectors, are needed to determine the optimal approach for clinical practice.

Background: The increasing detection of non-palpable breast lesions necessitates accurate preoperative localization to ensure complete excision while preserving healthy tissue and optimizing cosmetic outcomes. Traditional wire-guided localization (WL) has been the gold standard; however, it has several drawbacks, including patient discomfort and scheduling challenges. This study evaluates the accuracy and feasibility of radiofrequency identification (RFID) tag localization using the Hologic LOCalizer system as an alternative technique. Methods: This retrospective study included 258 consecutive patients who underwent image-guided RFID tag localization from March 2021 to February 2023. The primary outcome measured was the accuracy of tag placement, defined as within 10 mm of the target lesion on post-clip mammograms. Secondary outcomes included patient demographics, type and size of lesions, and re-excision rates. Results: A total of 297 RFID tags were placed, with 95.6% accurately positioned within the target range. The median target size was 29mm, with the most common abnormalities being mass lesions (64%). Among the 13 inaccurately placed tags (4.4%), all were identified preoperatively, with two requiring additional wire placements. Tags were successfully identified in 92% of specimen radiographs, and 8% of patients required re-excision due to positive or close margins. Notably, patients with multiple tags showed a higher incidence of re-excision. Conclusion: The LOCalizer RFID system demonstrated a high accuracy rate for preoperative localization of breast lesions, presenting a viable alternative to WL. This technique improves surgical scheduling flexibility and enhances patient comfort. Comparative studies with other wire-free localization technologies, such as magnetic seeds and radar reflectors, are needed to determine the optimal approach for clinical practice.