Clinical trial NCT05192161: Computational Medical Imaging and Prediction of Diffusion/FLAIR Mismatch in Stroke Patients
Official title: Computational Medical Imaging (Radiomics) and Prediction of Diffusion/FLAIR Mismatch in Stroke Patients
Study type: OBSERVATIONAL
Overall status: ACTIVE_NOT_RECRUITING
Conditions: Stroke
Lead sponsor: Fondation Hôpital Saint-Joseph
Sponsor class: OTHER
First posted: 2022-01-14
Enrollment: 35
Sex: ALL
Minimum age (years): 18
Standard ages: ADULT
OLDER_ADULT
Accepts healthy volunteers: no
Observational model: COHORT
Time perspective: RETROSPECTIVE
Sampling method: NON_PROBABILITY_SAMPLE
Study population: Patients referred for suspected stroke between January 1, 2016 and May 1, 2021 at Paris Saint Joseph Hospital.

Brief summary: Stroke is a public health issue and a priority for our institution. MRI plays an essential role in the management of stroke. In this context, the contribution of MRI is diagnostic, etiological and prognostic.

Among the MRI parameters evaluated in the acute phase of the stroke, the evaluation of the mismatch between the DIFFUSION and FLAIR sequences is crucial as it will directly contribute to the therapeutic decision. A FLAIR-diffusion mismatch, i.e., a lesion with a diffusion but not a FLAIR hypersignal, identifies patients whose time of onset of symptoms is probably less than 4.5 hours. It is therefore understandable that the main arterial recanalization techniques performed in the acute phase are primarily reserved for patients with a positive mismatch.

In current practice, mismatch assessment is performed subjectively, by visually comparing the two sequences, which is known to be the cause of a lack of reproducibility and diagnostic performance.

Computational medical imaging techniques ("radiomics") have recently gained momentum and offer the prospect of automated and therefore more reproducible analysis of medical imaging data. In stroke patients, radiomics extracted from FLAIR imaging could thus contribute to describe the "diffusion flair" mismatch in a continuous and objective way.

For the time being, data analysis cannot be performed in real time due to technical constraints. If it is proven that radiomics can reliably analyze the mismatch on the FLAIR sequence alone, the next step will be to make the analysis feasible in clinical routine (i.e. in a time frame adapted to the therapeutic management).


Eligibility criteria: Inclusion Criteria:

* Patient with age ≥ 18 years
* Patient with supra-tentorial stroke treated by mechanical thrombectomy and who had MRI imaging on admission before endovascular treatment at Paris Saint-Joseph Hospital
* Complete MRI protocol including Diffusion and FLAIR sequences
* French-speaking patient

Exclusion Criteria:

* Patient under guardianship or curatorship
* Patient deprived of liberty
* Patient under court protection
* Patient objecting to the use of his data for this research

Primary outcomes:
measure: ability of a computational medical imaging technique ("radiomics"), performed on the FLAIR sequence alone, to predict the FLAIR diffusion mismatch in patients with ischemic stroke
timeFrame: Day 1
Secondary outcomes:
measure: Inter-technique comparison of mismatch assessment between automated "radiomics" analysis and subjective visual analysis (currently performed in clinical routine)
timeFrame: Day 1
measure: Evaluation of the prognostic value of the scores obtained with the two methods
timeFrame: Month 3
Other outcomes:
Locations:
city: Lille
country: France
facility: CHRU Lille
city: Paris
country: France
facility: Groupe Hospitalier Paris Saint-Joseph
Study officials:
affiliation: Fondation Hôpital Saint-Joseph
name: Jerome HODEL, MD
role: PRINCIPAL_INVESTIGATOR
References:
citation: Powers WJ, Rabinstein AA, Ackerson T, Adeoye OM, Bambakidis NC, Becker K, Biller J, Brown M, Demaerschalk BM, Hoh B, Jauch EC, Kidwell CS, Leslie-Mazwi TM, Ovbiagele B, Scott PA, Sheth KN, Southerland AM, Summers DV, Tirschwell DL; American Heart Association Stroke Council. 2018 Guidelines for the Early Management of Patients With Acute Ischemic Stroke: A Guideline for Healthcare Professionals From the American Heart Association/American Stroke Association. Stroke. 2018 Mar;49(3):e46-e110. doi: 10.1161/STR.0000000000000158. Epub 2018 Jan 24.
citation: Thomalla G, Cheng B, Ebinger M, Hao Q, Tourdias T, Wu O, Kim JS, Breuer L, Singer OC, Warach S, Christensen S, Treszl A, Forkert ND, Galinovic I, Rosenkranz M, Engelhorn T, Kohrmann M, Endres M, Kang DW, Dousset V, Sorensen AG, Liebeskind DS, Fiebach JB, Fiehler J, Gerloff C; STIR and VISTA Imaging Investigators. DWI-FLAIR mismatch for the identification of patients with acute ischaemic stroke within 4.5 h of symptom onset (PRE-FLAIR): a multicentre observational study. Lancet Neurol. 2011 Nov;10(11):978-86. doi: 10.1016/S1474-4422(11)70192-2. Epub 2011 Oct 4.
citation: Qiu W, Kuang H, Nair J, Assis Z, Najm M, McDougall C, McDougall B, Chung K, Wilson AT, Goyal M, Hill MD, Demchuk AM, Menon BK. Radiomics-Based Intracranial Thrombus Features on CT and CTA Predict Recanalization with Intravenous Alteplase in Patients with Acute Ischemic Stroke. AJNR Am J Neuroradiol. 2019 Jan;40(1):39-44. doi: 10.3174/ajnr.A5918. Epub 2018 Dec 20.
citation: Chen Q, Xia T, Zhang M, Xia N, Liu J, Yang Y. Radiomics in Stroke Neuroimaging: Techniques, Applications, and Challenges. Aging Dis. 2021 Feb 1;12(1):143-154. doi: 10.14336/AD.2020.0421. eCollection 2021 Feb.
citation: Tang TY, Jiao Y, Cui Y, Zhao DL, Zhang Y, Wang Z, Meng XP, Yin XD, Yang YJ, Teng GJ, Ju SH. Penumbra-based radiomics signature as prognostic biomarkers for thrombolysis of acute ischemic stroke patients: a multicenter cohort study. J Neurol. 2020 May;267(5):1454-1463. doi: 10.1007/s00415-020-09713-7. Epub 2020 Feb 1.
citation: Feng R, Badgeley M, Mocco J, Oermann EK. Deep learning guided stroke management: a review of clinical applications. J Neurointerv Surg. 2018 Apr;10(4):358-362. doi: 10.1136/neurintsurg-2017-013355. Epub 2017 Sep 27.