Multi-phase CT-Angiography outperforms angiographic careggi collateral score and predicts functional outcome in acute ischemic stroke.

BACKGROUND: Collaterals are a strong determinant of clinical outcome in acute ischemic stroke (AIS) patients undergoing Endovascular Treatment (EVT). Careggi Collateral Score (CCS) is an angiographic score that demonstrated to be superior to the widely suggested ASITN/SIR score. Multi-phase CT-Angiography (mCTA) could be alternatively adopted for collateral assessment. We investigated whether mCTA had an equivalent predictive performance for functional outcome compared to CCS. METHODS: Consecutive AIS patients undergoing EVT for large vessel occlusion within 24 h from onset were analyzed. Receiver operating characteristic curves and multivariable logistic regression were investigated to evaluate the predictive performance of mCTA collateral score (range 0-5) and CCS (range 0-4) for good functional outcome (three-months modified Rankin Scale 0-2). RESULTS: We included 201 subjects (59.7% females, mean age 75), of whom 96 (47.7%) had good outcome at three-months. Both CCS (OR = 14.4, 95% CI = 6.3-33.8) and mCTA (OR = 23.8, 95% CI = 10.1-56.4) collateral scores were independent predictors of outcome. The AUC of CCS was 0.80 (95% CI 0.73-0.86) and the best cut-off was ≥ 3 (87% sensitivity, 71% specificity), while the AUC of mCTA collateral score was 0.84 (95% CI 0.78-0.90) with an optimal cut-off of ≥ 4 (85% sensitivity, 87% specificity). Patients with good mCTA collaterals experienced smaller (16.6 vs. 63.7 mL, p < 0.001) infarct lesion as compared to those with mCTA poor collaterals. CONCLUSION: mCTA discriminative ability for three-months 0-2 mRS was found to be comparable to CCS. mCTA appears a valid, non-invasive imaging modality for evaluating collaterals of AIS patients potentially eligible for EVT.

Exploring Augmented Reality Integration in Diagnostic Imaging: Myth or Reality?

This study delves into the transformative potential of integrating augmented reality (AR) within imaging technologies, shedding light on this evolving landscape. Through a comprehensive narrative review, this research uncovers a wealth of literature exploring the intersection between AR and medical imaging, highlighting its growing prominence in healthcare. AR's integration offers a host of potential opportunities to enhance surgical precision, bolster patient engagement, and customize medical interventions. Moreover, when combined with technologies like virtual reality (VR), artificial intelligence (AI), and robotics, AR opens up new avenues for innovation in clinical practice, education, and training. However, amidst these promising prospects lie numerous unanswered questions and areas ripe for exploration. This study emphasizes the need for rigorous research to elucidate the clinical efficacy of AR-integrated interventions, optimize surgical workflows, and address technological challenges. As the healthcare landscape continues to evolve, sustained research efforts are crucial to fully realizing AR's transformative impact in medical imaging. Systematic reviews on AR in healthcare also overlook regulatory and developmental factors, particularly in regard to medical devices. These include compliance with standards, safety regulations, risk management, clinical validation, and developmental processes. Addressing these aspects will provide a comprehensive understanding of the challenges and opportunities in integrating AR into clinical settings, informing stakeholders about crucial regulatory and developmental considerations for successful implementation. Moreover, navigating the regulatory approval process requires substantial financial resources and expertise, presenting barriers to entry for smaller innovators. Collaboration across disciplines and concerted efforts to overcome barriers will be essential in navigating this frontier and harnessing the potential of AR to revolutionize healthcare delivery.

Precision Workforce Management for Radiographers: Monitoring and Managing Competences with an Automatic Tool.

Optimizing work shifts in healthcare is crucial for maintaining high standards of service delivery and fostering professional development. This study delves into the emerging field of skill-oriented work shift optimization, focusing specifically on radiographers within the healthcare sector. Through the development of Skills Retention Monitoring (SRH), this research aims to enhance skill monitoring, workload management, and organizational performance. In this study, several key highlights emerged: (a) Introduction of the SRH tool: The SRH tool represents a resource-efficient solution that harnesses existing software infrastructure. A preliminary version, focusing on the radiographers' professional profile, was released, and after several months of use, it demonstrated effectiveness in optimizing work based on competency monitoring. (b) The SRH tool has thus demonstrated the capacity to generate actionable insights in the organizational context of radiographers. By generating weekly reports, the SRH tool streamlines activity management and optimizes resource allocation within healthcare settings. (c) Application of a Computer-Assisted Web Interviewing (CAWI) tool for pre-release feedback during a training event. (d) Strategic importance of a maintenance and monitoring plan: This plan, rooted in a continuous quality improvement approach and key performance indicators, ensures the sustained effectiveness of the SRH tool. (e) Strategic importance of a transfer plan: Involving professional associations and employing targeted questionnaires, this plan ensures the customization of the tool from the perspective of each profession involved. This is a crucial point, as it will enable the release of tool versions tailored to various professions operating within the hospital sector. As a side result, the tool could allow for a more tailored and personalized medicine both by connecting the insights gathered through the SRH tool with the right competencies for healthcare professionals and with individual patient data. This integration could lead to better-informed decision making, optimizing treatment strategies based on both patient needs and the specific expertise of the healthcare provider. Future directions include deploying the SRH tool within the Pisa hospital network and exploring integration with AI algorithms for further optimization. Overall, this research contributes to advancing work shift optimization strategies and promoting excellence in healthcare service delivery.

Enhancing patient safety in radiotherapy: Implementation of a customized electronic checklist for radiation therapists.

Introduction: The radiotherapy workflow involves the collaboration of multiple professionals and the execution of several steps to results in an effective treatment. In this study, we described the clinical implementation of an electronic checklist, developed to standardize the process of the chart review prior to the first treatment fraction by the radiation therapists (RTTs). Materials and Methods: A customized electronic checklist was developed based on the recommendations of American Association of Physicists in Medicine (AAPM) Task Groups 275 and 315 and integrated into the Record and Verify System (RVS). The checklist consisted of 16 items requiring binary (yes/no) responses, with mandatory completion and review by RTTs prior to treatment. The utility of the checklist and its impact on workflow were assessed by analysing checklist reports, and by soliciting feedback to RTTs through an anonymized survey. Results: During the first trial phase, from June to November 2023, 285 checklists were completed with a 98% compilation rate and 94.4% review rate. Forty errors were detected, mainly due to missing signed treatment plans and absence of Beam's Eye View documentation. Ninety percent of detected errors were fixed before the treatment start. In 4 cases, the problem could not be fixed before the first fraction, resulting in a suboptimal first treatment. The feedback survey showed that RTTs described the checklist as useful, with minimal impact on workload, and supported its implementation. Discussion: The introduction of a customized electronic checklist improved the detection and correction of errors, thereby enhancing patient safety. The positive response from RTTs and the minimal impact on workflow underscore the value of the checklist as standard practice in radiotherapy departments.

Hypoperfusion intensity ratio correlates with collaterals and predicts outcome and infarct volume in acute ischemic stroke patients.

BACKGROUND: Hypoperfusion Intensity Ratio (HIR) is associated with collaterals and outcome in acute ischemic stroke (AIS). We investigated whether a combined assessment of HIR and collaterals could provide an added value. METHODS: Retrospective single-center study, including AIS patients with large vessel occlusion and endovascular treatment 0-24 h from onset. Predictors of FIV and outcome (90 days modified Rankin Scale 0-1) were investigated with linear and logistic regression respectively. Subjects were stratified in three groups: poor collaterals (grade 0-3) with poor HIR (≥.4), good collaterals (grade 4-5) with poor HIR/poor collaterals with good HIR (<.4) and good collaterals with good HIR. RESULTS: We included 337 patients (median age 77, 53.1% males), of whom 100 (29.7%) had excellent outcome. One hundred and forty five patients with favourable collateral and HIR profiles had smaller infarct (median poor collaterals with poor HIR 41 mL, good collaterals with poor HIR/poor collaterals with good HIR 21 mL and good collaterals with good HIR 11 mL, p <.001) and higher rates of excellent outcome (poor collaterals with poor HIR 15.7%, good collaterals with poor HIR/poor collaterals with good HIR 26.2% and good collaterals with good HIR 39.3% p =.001). Logistic regression showed that patients with favourable collateral and HIR profiles had the highest odds of good outcome (OR: 3.83, 95% CI 1.62-9.08, p =.002). CONCLUSION: Collaterals and HIR are independent predictors of final infarct lesion and outcome in stroke patients and their integration provides an added value. These findings might inform clinical practice and future trials.