Abstract W MP13: Missed Imaging Diagnosis Without CT Perfusion May Affect Clinical Decision for TPA and Thrombectomy in Acute Stroke

Stroke ◽  
2014 ◽  
Vol 45 (suppl_1) ◽  
Author(s):  
Sarah W Meng ◽  
Xiang Liu ◽  
Michael Hewitt
Keyword(s):  
Decision Making ◽  
Acute Stroke ◽  
Clinical Decision Making ◽  
Ct Perfusion ◽  
Infarct Volume ◽  
Clinical Decision ◽  
Imaging Diagnosis ◽  
Imaging Protocol ◽  
Number Of Patients ◽  
Negative Imaging

Purpose: In a previous study, we found higher detection rate of 2nd and 3rd order vascular thrombosis when CT Perfusion (CTP) was performed as compared to non-contrast CT (NCCT) and CT angiography (CTA) alone. Additionally, a significant number of patients with acute infarct were reported as negative without CTP. In this study, we sought to determine whether missed imaging diagnosis without CTP might affect clinical decision making. Methods: A total of 758 cases were included in our previous study, with CTP deficits reported in all 71 cases with final infarct volume of 2.8 ml or above. Conversely, 23 of 96 (24%) cases without CTP were reported as negative. In the group without CTP, 7 of 10 patients who had 2nd or 3rd order vascular thromboses with a final infarct > 30cc were reported negative, whereas only 1 of 10 cases were missed in patients who had CTP but a negative NCCT. The treatment decisions at the time of stroke were reviewed for these patients. Results: In 10 cases with final infarct volume > 30ml reported negative without CTP, zero received TPA or thrombectomy. Conversely, in the same category, 5 of 10 cases with positive CTP received TPA (p = 0.041). There was also a higher rate of TPA or thrombectomy treatment in patients with a positive imaging diagnosis, both with CTP (13 of 71, 18.3%) and without CTP (28 of 73, 38.4%), as compared to the group reported negative without CTP (3 of 23, 13%, p = 0.059). Fewer cases in the CTP group received treatment as compared to cases reported positive without CTP. A possible reason is that the cases with CTP were from an earlier phase of our acute stroke program, when treatment tended to be more conservative. Conclusions: Our study finds discrepancies in decision making for TPA and thrombectomy in stroke cases with positive versus negative imaging diagnosis. The cases reported negative were less likely to receive treatment, including those with relatively large final infarct size (>30ml). We speculate that a negative imaging diagnosis may create doubt for clinical diagnosis in some cases. Adding CTP in the acute stroke imaging protocol will increase imaging diagnostic accuracy and exclude stroke mimics, therefore providing valuable information for treatment.

scholarly journals Sources of variability in computed tomography perfusion: implications for acute stroke management

2011 ◽  
Vol 30 (6) ◽  
pp. E8 ◽  
Author(s):  
Benjamin Zussman ◽  
Pascal Jabbour ◽  
Kiran Talekar ◽  
Richard Gorniak ◽  
Adam E. Flanders
Keyword(s):  
Decision Making ◽  
Data Acquisition ◽  
Acute Stroke ◽  
Clinical Decision Making ◽  
Ct Perfusion ◽  
Imaging Modality ◽  
Clinical Decision ◽  
Future Research ◽  
Original Research ◽  
Perfusion Study

Object Although dynamic, first-pass cerebral CT perfusion is used in the evaluation of acute ischemic stroke, a lack of standardization restricts the value of this imaging modality in clinical decision-making. The purpose of this study was to comprehensively review the reported sources of variability and error in cerebral CT perfusion results. Methods A systematic literature review was conducted, 120 articles were reviewed, and 23 published original research articles were included. Sources of variability and error were thematically categorized and presented within the context of the 3 stages of a typical CT perfusion study: data acquisition, postprocessing, and results interpretation. Results Seven factors that caused variability were identified and described in detail: 1) contrast media, the iodinated compound injected intravascularly to permit imaging of the cerebral vessels; 2) data acquisition rate, the number of images obtained by CT scan per unit time; 3) user inputs, the subjective selections that operators make; 4) observer variation, the failure of operators to repeatedly measure a perfusion parameter with precision; 5) software operational mode, manual, semiautomatic, or automatic; 6) software design, the mathematical algorithms used to perform postprocessing; and 7) value type, absolute versus relative values. Conclusions Standardization at all 3 stages of the CT perfusion study cycle is warranted. At present, caution should be exercised when interpreting CT perfusion results as these values may vary considerably depending on a variety of factors. Future research is needed to define the role of CT perfusion in clinical decision-making for acute stroke patients and to determine the clinically acceptable limits of variability in CT perfusion results.

Abstract WP42: CT Perfusion in Acute Stroke: Substantial Value Beyond Penumbra

Stroke ◽  
2013 ◽  
Vol 44 (suppl_1) ◽  
Author(s):  
Sarah W Meng ◽  
Michael Hewitt ◽  
Xiang Liu
Keyword(s):  
Acute Stroke ◽  
Ct Perfusion ◽  
Infarct Volume ◽  
Treatment Options ◽  
Vascular Occlusion ◽  
Diagnostic Sensitivity ◽  
Detection Sensitivity ◽  
Imaging Protocol ◽  
Vascular Thrombosis ◽  
Area Of Interest

Purpose: The role of CT Perfusion (CTP) in evaluation of acute stroke remains controversial, especially in determining ischemic penumbra and core infarct. Thus, our institution suspended CTP as part of the acute stroke imaging protocol, and now includes a non-contrast head CT (NCCT) and CT angiography (CTA) of the head and neck. We performed a retrospective review of cases using NCCT, CTA and CTP (CT-CTP) and cases using NCCT and CTA (CT-CTA protocol) at our institution from 2009 to 2011, to assess what, if any, substantial benefit CTP provides in the management of acute stroke. Methods: A total of 758 cases were reviewed, including 375 cases in the CT-CTP protocol and 383 cases in the CT-CTA protocol. Acute infarcts limited to the area covered by CTP were reviewed to compare the diagnostic sensitivity of the two protocols. Followup DWI or NCCT was used as the reference standard for final infarct size. Infarct volume was measured by freehand region of interest measurement. A subset group with final infarct volume > 30ml was also reviewed to explore the detection sensitivity of vascular thrombosis. Results: CTP deficits were reported in all 71 cases with a final infarct volume of 2.8 ml and above. Conversely, in the same category, 23 of 96 (24%) cases were reported as negative with CT-CTA protocol. Of the 10 cases with final infarct volume > 30ml and reported as negative in the CT- CTA protocol, 7of 10 had 2nd or 3rd order vascular thromboses, including 6 cases with infarct volume > 50ml. Only 2 of 45 thromboses were missed in the same category with CT-CTP protocol. Vascular thrombosis was missed in 1 of 10 cases with final infarct volume > 30ml in the CT-CTP protocol where NCCT was reported as negative but had positive CTP deficits. Conclusions: There is a substantially greater detection rate of 2nd and 3rd order vascular thrombosis when CTP is performed, including cases when NCCT is deemed negative. We speculate that a negative NCCT may provide false assurance, but that CTP deficits will guide attention to the area of interest, ultimately increasing detection of vascular occlusion and potentially influencing treatment options in the setting of acute stroke. Additionally, CTP significantly increases the diagnostic sensitivity of acute stroke compared to a combination of NCCT and CTA alone.

scholarly journals Can clinical audits be enhanced by pathway simulation and machine learning? An example from the acute stroke pathway

BMJ Open ◽  
2019 ◽  
Vol 9 (9) ◽  
pp. e028296 ◽  
Author(s):  
Michael Allen ◽  
Kerry Pearn ◽  
Thomas Monks ◽  
Benjamin D Bray ◽  
Richard Everson ◽  
...  
Keyword(s):  
Machine Learning ◽  
Acute Stroke ◽  
Clinical Pathway ◽  
Clinical Decision Making ◽  
Clinical Audit ◽  
Onset Time ◽  
Clinical Decision ◽  
Time Range ◽  
Audit Data ◽  
Number Of Patients

ObjectiveTo evaluate the application of clinical pathway simulation in machine learning, using clinical audit data, in order to identify key drivers for improving use and speed of thrombolysis at individual hospitals.DesignComputer simulation modelling and machine learning.SettingSeven acute stroke units.ParticipantsAnonymised clinical audit data for 7864 patients.ResultsThree factors were pivotal in governing thrombolysis use: (1) the proportion of patients with a known stroke onset time (range 44%–73%), (2) pathway speed (for patients arriving within 4 hours of onset: per-hospital median arrival-to-scan ranged from 11 to 56 min; median scan-to-thrombolysis ranged from 21 to 44 min) and (3) predisposition to use thrombolysis (thrombolysis use ranged from 31% to 52% for patients with stroke scanned with 30 min left to administer thrombolysis). A pathway simulation model could predict the potential benefit of improving individual stages of the clinical pathway speed, whereas a machine learning model could predict the benefit of ‘exporting’ clinical decision making from one hospital to another, while allowing for differences in patient population between hospitals. By applying pathway simulation and machine learning together, we found a realistic ceiling of 15%–25% use of thrombolysis across different hospitals and, in the seven hospitals studied, a realistic opportunity to double the number of patients with no significant disability that may be attributed to thrombolysis.ConclusionsNational clinical audit may be enhanced by a combination of pathway simulation and machine learning, which best allows for an understanding of key levers for improvement in hyperacute stroke pathways, allowing for differences between local patient populations. These models, based on standard clinical audit data, may be applied at scale while providing results at individual hospital level. The models facilitate understanding of variation and levers for improvement in stroke pathways, and help set realistic targets tailored to local populations.

scholarly journals Machine learning to guide clinical decision-making in abdominal surgery—a systematic literature review

2021 ◽  
Author(s):  
Jonas Henn ◽  
Andreas Buness ◽  
Matthias Schmid ◽  
Jörg C. Kalff ◽  
Hanno Matthaei
Keyword(s):  
Machine Learning ◽  
Decision Making ◽  
Literature Review ◽  
Abdominal Surgery ◽  
Clinical Decision Making ◽  
Clinical Decision ◽  
Number Of Patients ◽  
Pubmed Database ◽  
Computer Scientists ◽  
Number Of Publications

Abstract Purpose An indication for surgical therapy includes balancing benefits against risk, which remains a key task in all surgical disciplines. Decisions are oftentimes based on clinical experience while guidelines lack evidence-based background. Various medical fields capitalized the application of machine learning (ML), and preliminary research suggests promising implications in surgeons’ workflow. Hence, we evaluated ML’s contemporary and possible future role in clinical decision-making (CDM) focusing on abdominal surgery. Methods Using the PICO framework, relevant keywords and research questions were identified. Following the PRISMA guidelines, a systemic search strategy in the PubMed database was conducted. Results were filtered by distinct criteria and selected articles were manually full text reviewed. Results Literature review revealed 4,396 articles, of which 47 matched the search criteria. The mean number of patients included was 55,843. A total of eight distinct ML techniques were evaluated whereas AUROC was applied by most authors for comparing ML predictions vs. conventional CDM routines. Most authors (N = 30/47, 63.8%) stated ML’s superiority in the prediction of benefits and risks of surgery. The identification of highly relevant parameters to be integrated into algorithms allowing a more precise prognosis was emphasized as the main advantage of ML in CDM. Conclusions A potential value of ML for surgical decision-making was demonstrated in several scientific articles. However, the low number of publications with only few collaborative studies between surgeons and computer scientists underpins the early phase of this highly promising field. Interdisciplinary research initiatives combining existing clinical datasets and emerging techniques of data processing may likely improve CDM in abdominal surgery in the future.

scholarly journals Effect of different thresholds for CT perfusion volumetric analysis on estimated ischemic core and penumbral volumes

PLoS ONE ◽  
2021 ◽  
Vol 16 (4) ◽  
pp. e0249772
Author(s):  
Simo Karhi ◽  
Olli Tähtinen ◽  
Joona Aherto ◽  
Hanna Matikka ◽  
Hannu Manninen ◽  
...  
Keyword(s):  
Clinical Decision Making ◽  
Ct Perfusion ◽  
Infarct Volume ◽  
Automated Analysis ◽  
Clinical Decision ◽  
Volumetric Analysis ◽  
Anterior Circulation ◽  
Multicenter Studies ◽  
Computed Tomographic ◽  
Ischemic Core

Purpose This single-center study compared three threshold settings for automated analysis of the ischemic core (IC) and penumbral volumes using computed tomographic perfusion, and their accuracy for predicting final infarct volume (FIV) in patients with anterior circulation acute ischemic stroke (AIS). Methods Fifty-two consecutive AIS patients undergoing mechanical thrombectomy (November 2015–March 2018) were included. Perfusion images were retrospectively analyzed using a single CT Neuro perfusion application (syngo.via 4.1, Siemens Healthcare GmbH). Three threshold values (S1–S3) were derived from another commercial package (RAPID; iSchema View) (S1), up-to-date syngo.via default values (S2), and adapted values for syngo.via from a reference study (S3). The results were compared with FIV determined by non-contrast CT. Results The median IC volume (mL) was 24.6 (interquartile range: 13.7–58.1) with S1 and 30.1 (20.1–53.1) with S2/S3. After removing the contralateral hemisphere from the analysis, the median IC volume decreased by 1.33(0–3.14) with S1 versus 9.13 (6.24–14.82) with S2/S3. The median penumbral volume (mL) was 74.52 (49.64–131.91), 77.86 (46.56–99.23), and 173.23 (125.86–200.64) for S1, S2, and S3, respectively. Limiting analysis to the affected hemisphere, the penumbral volume decreased by 1.6 (0.13–9.02), 19.29 (12.59–26.52), and 58.33 mL (45.53–74.84) for S1, S2, and S3, respectively. The correlation between IC and FIV was highest in patients with successful recanalization (n = 34, r = 0.784 for S1; r = 0.797 for S2/S3). Conclusion Optimizing thresholds significantly improves the accuracy of estimated IC and penumbral volumes. Current recommended values produce diversified results. International guidelines based on larger multicenter studies should be established to support the standardization of volumetric analysis in clinical decision-making.

Clinical Decision Making and Oral Motor Treatments

ASHA Leader ◽  
2005 ◽  
Vol 10 (8) ◽  
pp. 8-35 ◽  
Author(s):  
Heather M. Clark
Keyword(s):  
Decision Making ◽  
Clinical Decision Making ◽  
Clinical Decision ◽  
Oral Motor

Debates in Dysphagia Management: How Do You Use Evidence-Based Practice in Your Dysphagia Patient Care?

2011 ◽  
Vol 20 (4) ◽  
pp. 121-123
Author(s):  
Jeri A. Logemann
Keyword(s):  
Decision Making ◽  
Patient Care ◽  
Clinical Outcomes ◽  
Clinical Judgment ◽  
Clinical Decision Making ◽  
Evidence Based Practice ◽  
Clinical Decision ◽  
Evidence Based ◽  
Clinical Method ◽  
Do So

Evidence-based practice requires astute clinicians to blend our best clinical judgment with the best available external evidence and the patient's own values and expectations. Sometimes, we value one more than another during clinical decision-making, though it is never wise to do so, and sometimes other factors that we are unaware of produce unanticipated clinical outcomes. Sometimes, we feel very strongly about one clinical method or another, and hopefully that belief is founded in evidence. Some beliefs, however, are not founded in evidence. The sound use of evidence is the best way to navigate the debates within our field of practice.

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