Real‐time diffusion‐perfusion mismatch analysis in acute stroke

Abstract

Diffusion-perfusion mismatch can be used to identify acute stroke patients that could benefit from reperfusion therapies. Early assessment of the mismatch facilitates necessary diagnosis and treatment decisions in acute stroke. We developed the RApid processing of PerfusIon and Diffusion (RAPID) for unsupervised, fully automated processing of perfusion and diffusion data for the purpose of expedited routine clinical assessment. The RAPID system computes quantitative perfusion maps (cerebral blood volume, CBV; cerebral blood flow, CBF; mean transit time, MTT; and the time until the residue function reaches its peak, T max ) using deconvolution of tissue and arterial signals. Diffusion-weighted imaging/perfusionweighted imaging (DWI/PWI) mismatch is automatically determined using infarct core segmentation of ADC maps and perfusion deficits segmented from T max maps. The performance of RAPID was evaluated on 63 acute stroke cases, in which diffusion and perfusion lesion volumes were outlined by both a human reader and the RAPID system. The correlation of outlined lesion volumes obtained from both methods was r 2 ¼ 0.99 for DWI and r 2 ¼ 0.96 for PWI. For mismatch identification, RAPID showed 100% sensitivity and 91% specificity. The mismatch information is made available on the hospital's PACS within 5-7 min. Results indicate that the automated system is sufficiently accurate and fast enough to be used for routine care as well as in clinical trials.

Brazilian guidelines for endovascular treatment of patients with acute ischemic stroke

“…All patients evaluated in EXTEND-IA used the RAPID evaluation as an inclusion criterion to determine the presence of penumbral mismatch on CT perfusion 31 . The SWIFT-PRIME also used the same strategy for the first 71 of 196 patients but later adopted the ASPECTS core criteria to ensure quicker therapy and higher enrollment.…”

Performance and Predictive Value of a User-Independent Platform for CT Perfusion Analysis: Threshold-Derived Automated Systems Outperform Examiner-Driven Approaches in Outcome Prediction of Acute Ischemic Stroke

“…RAPID is an operator-independent image processing and visualization tool operating on standardized DICOM data and configured for entirely automated image processing. 18 As an extension of earlier iterations compiled for analysis of MRI diffusion and perfusion imaging, the current implementation further permits CTP postprocessing carried through a computational pipeline similar to that initially described. Briefly, following preprocessing steps correcting rigid-body motion, arterial input function selection is performed and deconvolved from the voxel time-attenuation course using a delay-insensitive algorithm for isolation of the tissue residue function.…”

“…18 Both CBV and CBF have been proposed as estimates of irreversibly infarcted (core) tissues, with past investigations describing both absolute and relative (rCBV, rCBF) thresholds for the detection of infarct core. 19 For the purposes of this study, separate estimates were supplied for each, thresholded at relative rCBF or rCBV Ͻ30% normal.…”

“…15,16 The potential for disparate results and the variability in accuracy among competing software platforms have been the subject of recent studies and were thoroughly expounded in a comparative analysis by Kudo et al 17 In light of recent reports, the primary objective of this study were to examine the predictive performance of several user-defined approaches to NCCT, CTA, and CTP analysis, by comparison with a fast, vendor-and operator-independent computational tool using fully automated lesion segmentation and pixel-wise parametric thresholding for semiquantitation (RApid processing of PerfusIon and Diffusion [RAPID]). 18 The objective of our study was to evaluate these tools to determine their ability to predict 90-day favorable clinical outcome in patients with AIS.…”

Computational Analysis: A Bridge to Translational Stroke Treatment

“…However, a recent study has detailed several critical drawbacks of this method [ 64 ] . When using DWI and PWI, visual (subjective) estimation of the penumbra volume is performed [ 62,63 ] , or ROIs detected from one modality are manually traced on the other to estimate the mismatch [ 65 ] , or manual registration between these two imaging modalities is performed to measure the mismatch [ 66 ] . These approaches are neither statistically reliable nor objective.…”