Skip to main content
Advertisement

Main menu

  • Home
  • Content
    • Current Issue
    • Accepted Manuscripts
    • Article Preview
    • Past Issue Archive
    • Video Articles
    • AJNR Case Collection
    • Case of the Week Archive
    • Case of the Month Archive
    • Classic Case Archive
  • Special Collections
    • AJNR Awards
    • ASNR Foundation Special Collection
    • Most Impactful AJNR Articles
    • Photon-Counting CT
    • Spinal CSF Leak Articles (Jan 2020-June 2024)
  • Multimedia
    • AJNR Podcasts
    • AJNR SCANtastic
    • Trainee Corner
    • MRI Safety Corner
    • Imaging Protocols
  • For Authors
    • Submit a Manuscript
    • Submit a Video Article
    • Submit an eLetter to the Editor/Response
    • Manuscript Submission Guidelines
    • Statistical Tips
    • Fast Publishing of Accepted Manuscripts
    • Graphical Abstract Preparation
    • Imaging Protocol Submission
    • Author Policies
  • About Us
    • About AJNR
    • Editorial Board
    • Editorial Board Alumni
  • More
    • Become a Reviewer/Academy of Reviewers
    • Subscribers
    • Permissions
    • Alerts
    • Feedback
    • Advertisers
    • ASNR Home

User menu

  • Alerts
  • Log in

Search

  • Advanced search
American Journal of Neuroradiology
American Journal of Neuroradiology

American Journal of Neuroradiology

ASHNR American Society of Functional Neuroradiology ASHNR American Society of Pediatric Neuroradiology ASSR
  • Alerts
  • Log in

Advanced Search

  • Home
  • Content
    • Current Issue
    • Accepted Manuscripts
    • Article Preview
    • Past Issue Archive
    • Video Articles
    • AJNR Case Collection
    • Case of the Week Archive
    • Case of the Month Archive
    • Classic Case Archive
  • Special Collections
    • AJNR Awards
    • ASNR Foundation Special Collection
    • Most Impactful AJNR Articles
    • Photon-Counting CT
    • Spinal CSF Leak Articles (Jan 2020-June 2024)
  • Multimedia
    • AJNR Podcasts
    • AJNR SCANtastic
    • Trainee Corner
    • MRI Safety Corner
    • Imaging Protocols
  • For Authors
    • Submit a Manuscript
    • Submit a Video Article
    • Submit an eLetter to the Editor/Response
    • Manuscript Submission Guidelines
    • Statistical Tips
    • Fast Publishing of Accepted Manuscripts
    • Graphical Abstract Preparation
    • Imaging Protocol Submission
    • Author Policies
  • About Us
    • About AJNR
    • Editorial Board
    • Editorial Board Alumni
  • More
    • Become a Reviewer/Academy of Reviewers
    • Subscribers
    • Permissions
    • Alerts
    • Feedback
    • Advertisers
    • ASNR Home
  • Follow AJNR on Twitter
  • Visit AJNR on Facebook
  • Follow AJNR on Instagram
  • Join AJNR on LinkedIn
  • RSS Feeds

AJNR is seeking candidates for the AJNR Podcast Editor. Read the position description.

Research ArticleBrain
Open Access

Stroke Mismatch Volume with the Use of ABC/2 Is Equivalent to Planimetric Stroke Mismatch Volume

M. Luby, J. Hong, J.G. Merino, J.K. Lynch, A.W. Hsia, A. Magadán, S.S. Song, L.L. Latour and S. Warach
American Journal of Neuroradiology October 2013, 34 (10) 1901-1907; DOI: https://doi.org/10.3174/ajnr.A3476
M. Luby
aFrom the National Institute of Neurological Disorders and Stroke (M.L., J.H., J.G.M., J.K.L., A.W.H., A.M., L.L.L., S.W.); Bethesda, Maryland
  • Find this author on Google Scholar
  • Find this author on PubMed
  • Search for this author on this site
J. Hong
aFrom the National Institute of Neurological Disorders and Stroke (M.L., J.H., J.G.M., J.K.L., A.W.H., A.M., L.L.L., S.W.); Bethesda, Maryland
  • Find this author on Google Scholar
  • Find this author on PubMed
  • Search for this author on this site
J.G. Merino
aFrom the National Institute of Neurological Disorders and Stroke (M.L., J.H., J.G.M., J.K.L., A.W.H., A.M., L.L.L., S.W.); Bethesda, Maryland
bJohns Hopkins Community Physicians (J.G.M.), Bethesda, Maryland
  • Find this author on Google Scholar
  • Find this author on PubMed
  • Search for this author on this site
J.K. Lynch
aFrom the National Institute of Neurological Disorders and Stroke (M.L., J.H., J.G.M., J.K.L., A.W.H., A.M., L.L.L., S.W.); Bethesda, Maryland
  • Find this author on Google Scholar
  • Find this author on PubMed
  • Search for this author on this site
A.W. Hsia
aFrom the National Institute of Neurological Disorders and Stroke (M.L., J.H., J.G.M., J.K.L., A.W.H., A.M., L.L.L., S.W.); Bethesda, Maryland
bJohns Hopkins Community Physicians (J.G.M.), Bethesda, Maryland
  • Find this author on Google Scholar
  • Find this author on PubMed
  • Search for this author on this site
A. Magadán
aFrom the National Institute of Neurological Disorders and Stroke (M.L., J.H., J.G.M., J.K.L., A.W.H., A.M., L.L.L., S.W.); Bethesda, Maryland
  • Find this author on Google Scholar
  • Find this author on PubMed
  • Search for this author on this site
S.S. Song
dCedars Sinai Medical Center (S.S.S.), Los Angeles, California
  • Find this author on Google Scholar
  • Find this author on PubMed
  • Search for this author on this site
L.L. Latour
aFrom the National Institute of Neurological Disorders and Stroke (M.L., J.H., J.G.M., J.K.L., A.W.H., A.M., L.L.L., S.W.); Bethesda, Maryland
  • Find this author on Google Scholar
  • Find this author on PubMed
  • Search for this author on this site
S. Warach
aFrom the National Institute of Neurological Disorders and Stroke (M.L., J.H., J.G.M., J.K.L., A.W.H., A.M., L.L.L., S.W.); Bethesda, Maryland
eNINDS Natural History of Stroke Investigators (S.W.), Bethesda, Maryland.
  • Find this author on Google Scholar
  • Find this author on PubMed
  • Search for this author on this site
  • Article
  • Figures & Data
  • Info & Metrics
  • Responses
  • References
  • PDF
Loading

Abstract

BACKGROUND AND PURPOSE: In the clinical setting, there is a need to perform mismatch measurements quickly and easily on the MR imaging scanner to determine the specific amount of treatable penumbra. The objective of this study was to quantify the agreement of the ABC/2 method with the established planimetric method.

MATERIALS AND METHODS: Patients (n = 193) were selected from the NINDS Natural History Stroke Registry if they 1) were treated with standard intravenous rtPA, 2) had a pretreatment MR imaging with evaluable DWI and PWI, and 3) had an acute ischemic stroke lesion. A rater placed the linear diameters to measure the largest DWI and MTT lesion areas in 3 perpendicular axes—A, B, and C—and then used the ABC/2 formula to calculate lesion volumes. A separate rater measured the planimetric volumes. Multiple mismatch thresholds were used, including MTT volume − DWI volume ≥50 mL versus ≥60 mL and (MTT volume − DWI volume)/MTT volume ≥20% versus MTT/DWI = 1.8.

RESULTS: Compared with the planimetric method, the ABC/2 method had high sensitivity (0.91), specificity (0.90), accuracy (0.91), PPV (0.90), and NPV (0.91) to quantify mismatch by use of the ≥50 mL definition. The Spearman correlation coefficients were 0.846 and 0.876, respectively, for the DWI and MTT measurements. The inter-rater Bland-Altman plots demonstrated 95%, 95%, and 97% agreement for the DWI, MTT, and mismatch measurements.

CONCLUSIONS: The ABC/2 method is highly reliable and accurate for quantifying the specific amount of MR imaging–determined mismatch and therefore is a potential tool to quickly calculate a treatable mismatch pattern.

ABBREVIATIONS:

CI
confidence interval
IQR
interquartile range
NPV
negative predictive value
PPV
positive predictive value
SD
standard deviation

In the clinical setting, there is a need to perform quantitative mismatch measurements quickly and easily to determine the specific amount of treatable penumbra. The ABC/2 method of measuring quantitative mismatch is a viable option because it can be performed immediately on the MR imaging scanner and has precedence in other diseases. Prior studies by use of the ABC/2 method to measure intracerebral hemorrhage or subdural hematoma volumes have been extensively applied and validated.1⇓–3 Kothari et al1 demonstrated that the ABC/2 method had excellent correlation with the planimetric method when applied to the measurements of intracerebral hemorrhage volumes. Furthermore, they demonstrated excellent inter-rater and intrarater reliability for the ABC/2 method.1 Gebel et al2 adapted the ABC/2 method successively to measure subdural hematoma volumes and demonstrated excellent correlation with a computerized technique. Huttner et al3 applied the ABC/2 method to more complicated intracerebral hemorrhage patterns and found that modification of the formula to ABC/3 produced more accurate measurements. In acute ischemic stroke, automated mismatch measurements by use of postprocessing software are advantageous4 for quantifying mismatch but are not generally available. Quality or format limitations of some scans may prohibit automated software from producing usable mismatch results. The feasibility of qualitative evaluation of mismatch on MR imaging before thrombolysis has been presented.5,6 However, in recent stroke clinical trials, specific imaging thresholds for mismatch beyond visual confirmation were required to make enrollment decisions.7⇓⇓⇓⇓–12 Optimization of thresholds including mismatch of >20%10,11 and PWI/DWI >1.8,12 have been investigated retrospectively by many investigators to apply these conditions prospectively for automated measurement.10⇓–12 Validation of the ABC/2 mismatch method may prove to be less challenging than validating the numeric methods for automated mismatch measurements. Furthermore, the ABC/2 method is a possible alternative to automated methods when image quality restricts their usage. However, the agreement of the ABC/2 method with the planimetric method has not been fully defined. Sims et al13 established that the ABC/2 method provided the best estimation of infarction and MTT volumes. The prior study demonstrated a high PPV of 92%; however, the results had a poor NPV of 33%.13 Pedraza et al14 recommended that a larger study looking at broader range of mismatch volumes and clinical outcomes ultimately should be performed. Vogt et al15 used the ABC/2 method mainly in CT scans in >1800 patients with ischemic stroke and hemorrhage but demonstrated in a subset of MR imaging scans that their infarct volume results were stable regardless of imaging technique. Warach et al16 demonstrated a difference in favorable clinical outcome in desmoteplase-treated patients versus placebo-treated patients in a post hoc analysis of the Desmoteplase in Acute Ischemic Stroke Trial-2 when applying a specific mismatch threshold of >60 mL. However, no study has compared these various mismatch definitions across both the ABC/2 and planimetric methods to quantify their agreement and feasibility for application in the clinical trial setting. Therefore, the primary focus of this study was to compare the agreement across definitions when quantifying the amount of mismatch by use of both the ABC/2 and planimetric methods.

The objectives of this study were to compare the ABC/2 and planimetric methods to determine the agreement between the mismatch volumes and resulting classifications. Our hypotheses were 1) the ABC/2 measurements were equivalent to the planimetric measurements and therefore the ABC/2 method was an accurate tool for quick quantification of treatable mismatch patterns, and 2) the ABC/2 mismatch classifications predicted the same clinical outcomes as the planimetric mismatch classifications.

Materials and Methods

Patients

This is an analysis of data from the National Institute of Neurological Disorders and Stroke Natural History registry. The NINDS Natural History registry is a dataset formed from 2 acute stroke centers: Suburban Hospital in Bethesda, Maryland, and Medstar Washington Hospital Center in Washington, DC. The appropriate ethics and institutional review boards approved the study. For this study, all patients were treated with standard intravenous rtPA within 3 hours of time last known well between December 2000 and October 2009. Patients were included if they 1) were treated with standard intravenous rtPA, 2) had a pretreatment MR imaging with evaluable DWI and PWI, and 3) had an acute ischemic stroke lesion.

Imaging Series

Imaging was performed by use of 1.5T (TwinSpeed; GE Healthcare, Milwaukee, Wisconsin) or 3T (Achieva; Philips, Best, the Netherlands) clinical MR imaging scanners. DWI and PWI series were acquired co-localized over the entire brain with a superior to inferior coverage of 14 cm. Typical imaging parameters for DWI spin-echo echo-planar series included either 40–3.5-mm- or 20–7-mm-thick contiguous axial oblique sections with b = 0 and b = 1000 seconds/mm2, trace or isotropically weighted, TR/TE = 6000–7000/72–90 ms, acquisition matrix of 64 × 64–128 × 128, and 22 cm FOV. The PWI was a dynamic susceptibility contrast series with the use of a single dose of 0.1 mmol/kg of gadolinium (Magnevist; Bayer Schering Pharma, Wayne, New Jersey). Typical imaging parameters for PWI gradient echo-planar series included 20 contiguous axial oblique sections with single-dose gadolinium contrast injection of 0.1 mmol/kg through a power injector by using 25–40 phase measurements, TR/TE = 2000–2200/45 ms, acquisition matrix of 64 × 64–128 × 128, 7-mm section thickness, and 22-cm FOV.

Image Analysis

ABC/2 Volume Method for Quantitative Mismatch.

A rater (J.H.) measured the ABC/2 volume of DWI and MTT lesions by using a DICOM image viewer. After optimizing the window level settings, the 2 longest perpendicular linear diameters (A and B) on the section where the abnormality on DWI appeared largest were measured (Fig 1A). The same process was repeated on the section with the largest area of MTT abnormality (Fig 1B). With the use of these diameters, the product of the section thickness, and the total number of sections containing the lesion (C), the ABC/2 DWI and MTT volumes were calculated with the formula: volume = ABC/2. For discontinuous lesions, only the largest lesion area was measured. Multiple measurements were not performed across the discontinuous lesions. However, if the lesion was continuous and included multiple vascular territories, the measurement included the entire lesion area. For punctate lesions, the largest lesion area was measured.

Fig 1.
  • Download figure
  • Open in new tab
  • Download powerpoint
Fig 1.

Corresponding measurements for the ABC/2 method (A, DWI = 116.1 mL; B, MTT = 194.7 mL) and planimetric method (C, DWI = 116.2 mL; D, MTT = 248.4 mL) on paired sections placed independently by 2 different readers.

Planimetric Volume Method for Quantitative Mismatch.

A rater (M.L.) with extensive experience and established rater reliability statistics measured the lesion volumes on the DWI and MTT maps by using a semi-automated quantitative, planimetric method in Cheshire (Boulder, Colorado).17 The intrarater and inter-rater reliability of the planimetric measurements of DWI and MTT was validated as a highly consistent and repeatable method by use of Cheshire in the Luby et al study.17 Lesion areas were segmented on a section-by-section basis, with user-selected seed points followed by user-driven editing (Fig 1C, -D).

Thresholds for Quantitative Mismatch.

Patients were classified as having a quantitative mismatch when the difference in the volumes on the MTT and the DWI was ≥50 mL2 versus ≥60 mL16 and (MTT volume − DWI volume)/MTT volume ≥20%10,11 versus MTT/DWI ≥1.8.12

Inter-Rater Reliability of ABC/2 Volume Method.

For the purposes of determining inter-rater reliability of the ABC/2 method, the rater (M.L.) who performed the planimetric volume measurements independently measured the ABC/2 lesion volumes on DWI and MTT, blinded to the quantitative results already generated for the study.

Statistical Analysis

The following analyses were performed: 1) lesion volumes for the ABC/2 and planimetric methods and associated mismatch classifications, based on the MTT−DWI ≥50 mL versus ≥60 mL and (MTT volume − DWI volume)/MTT volume ≥20% versus MTT/DWI ≥1.8 definitions, 2) agreement of mismatch classifications as determined by the ABC/2 and planimetric methods, 3) inter-rater reliability measures for the DWI and MTT and measurements by use of the ABC/2 method, and 4) functional outcome rates by use of modified Rankin Scale scores among individuals across the ABC/2 and planimetric methods. SPSS Statistics (v17.0; SPSS, Chicago, Illinois) was used for all statistical analyses.

For the lesion volume statistics, only cases with positive lesions, that is, >0 mL volumes, were included. Values are reported as mean (±SD) or median (IQR, 25–75) when appropriate. Agreement rates were defined as the number of cases agreed divided by the total number of cases (n = 193) except as noted. Linear regression of volumes was performed to demonstrate the correlation between the ABC/2 and planimetric measurements. The Bland-Altman plots were generated to display the spread of the lesion volumes and the limits of agreement between the ABC/2 and planimetric measurements, specifically to illustrate how many of the measurements were within 2 SD from the mean volume difference. Inter-rater reliability of the lesion volumes was quantified by Spearman correlation coefficients and Bland-Altman plots. The Bland-Altman plots were generated to display the spread of the lesion volumes and the limits of agreement between the 2 independent sets of ABC/2 measurements. Cohen κ coefficients were calculated. The Bland-Altman and linear regression plots were on the logarithmic scale. Contingency (2 × 2) tables were used to calculate specificity, sensitivity, accuracy, PPV, and NPV of the ABC/2 method compared with the planimetric method.

Results

Patients

From December 2000 through October 31, 2009, 385 patients were treated with standard intravenous rtPA. Of these, 234 patients had a pretreatment MR imaging. Forty-one patients were excluded because they did not include PWI (n = 18) or the DWI and MTT maps were not available or not evaluable (n = 23). The final sample in this study includes 193 patients. In 143 patients, the MR imaging was performed at 1.5T and in 50 at 3T. Fifty-two percent of the patients were women (n = 102). The mean age of the patients was 70.8 (±15.7) years, and the median time from stroke onset to baseline MR imaging was 103 (IQR, 79–128) minutes. The median baseline NIHSS score in the 192 patients for whom these data are available was 9 (IQR, 4–18).

ABC/2 Volumes

Using the ABC/2 method, DWI (n = 184), MTT (n = 170), and mismatch (MTT-DWI, n = 150) median volumes were 18.9 mL (IQR, 3.1–60.0), 116.3 mL (IQR, 33.0–249.5), and 78.9 mL (IQR, 26.8–183.6), respectively. Overall, 48.7% of patients of the entire sample (n = 94/193) were classified as having a mismatch by the ABC/2 method by use of the MTT−DWI ≥50 mL definition. Table 1 contains the volume statistics for the 94 patients with mismatch ≥50 mL versus the 56 patients without measurable mismatch. Forty-four percent of patients (n = 85/193) were classified as having a mismatch by use of the MTT−DWI ≥60 mL definition. Seventy-four percent of patients (n = 142/193) were classified as having a mismatch by use of the MTT−DWI ≥20% definition versus 60% (n = 116/193) by use of the MTT/DWI ≥1.8 definition.

View this table:
  • View inline
  • View popup
Table 1:

Comparison of volume statistics between patients classified as mismatch versus no mismatch by use of the 50-mL mismatch definition for the ABC/2 and planimetric methods

Planimetric Volumes

With the use of the planimetric volume method, DWI (n = 186), MTT (n = 167), and mismatch (MTT-DWI, n = 154) median volumes were 12.4 mL (IQR, 2.6–51.8), 103.9 mL (IQR, 30.7–208.6), and 74.2 mL (IQR, 21.8–165.9), respectively. Overall, 48% of patients (n = 92/193) were classified as having a mismatch by the planimetric volume method by use of the MTT−DWI ≥50 mL definition. Table 1 contains the volume statistics for the 92 patients with mismatch ≥50 mL versus the 62 patients without measurable mismatch. Forty-five percent of patients (n = 87/193) were classified as having a mismatch by use of the MTT−DWI ≥60 mL definition. Seventy-four percent of patients (n = 142/193) were classified as having a mismatch by use of the MTT−DWI ≥20% definition versus 60% (n = 116/193) by use of the MTT/DWI ≥1.8 definition.

Comparison of ABC/2 and Planimetric Measurements

The linear regression plots (Fig 2) of ABC/2 with planimetric measurements are displayed for DWI (Fig 2A), MTT (Fig 2B), and mismatch (Fig 2C). The plots are on the logarithmic scale. The R2, slope and confidence intervals for DWI, MTT, and mismatch are 0.752, 0.867 (CI, 0.83–0.99), 0.822, 0.906 (CI, 0.82–0.95), and 0.69, 0.83 (CI, 0.65–0.83), respectively. The Bland-Altman plots (Fig 3) of the ABC/2 versus planimetric measurements demonstrated that 93.4%, 94.9%, and 93.3% for the DWI, MTT, and mismatch measurements were within the thresholds defined by 2 SD from the mean differences. The Spearman correlation coefficients were 0.84 and 0.87 for the DWI and MTT measurements, respectively (P < .01), between the ABC/2 and planimetric methods. The sensitivity (0.91), specificity (0.90), accuracy (0.91), PPV (0.90), and NPV (0.91) were excellent for the ABC/2 method by use of the planimetric mismatch definition ≥50 mL. Volume statistics for the discrepant patients (n = 17) are included in Table 2. On the basis of the ABC/2 measurements of cases FN 6, FN 7, and FN 8, treatment decisions requiring a mismatch may have changed. However, there is a positive mismatch for the remaining 14 discrepant patients across both methods; therefore, changes in treatment decisions for thrombolysis are not likely.

Fig 2.
  • Download figure
  • Open in new tab
  • Download powerpoint
Fig 2.

Linear regression plots of ABC/2 with planimetric measurements displaying the respective regression lines with R2 and slope values for DWI (A), MTT (B), and mismatch (C). Plots are on the logarithmic scale.

Fig 3.
  • Download figure
  • Open in new tab
  • Download powerpoint
Fig 3.

Bland-Altman plots of the ABC/2 and planimetric volume measurements demonstrate the difference between the log volume of the planimetric measurement and the log volume of the ABC/2 measurement over the mean for DWI (A), MTT (B), and mismatch (C). Threshold lines above and below plots represent values that are 2 SD from the mean difference. Plots are on the logarithmic scale.

View this table:
  • View inline
  • View popup
Table 2:

Volume statistics for discrepant patients (n = 17, nine false-positives and eight false-negatives) on the basis of the ABC/2 method compared with the planimetric method by use of the mismatch definition ≥50 mL

Correlation Between Mismatch and Functional Outcome

Patients who were classified with a positive mismatch by visual or ABC/2 methods were more likely to have a good outcome as defined by modified Rankin Scale score = 0 or 1 (Table 3). The median last follow-up modified Rankin Scale score was 3 (IQR, 1–5), on the basis of the available data (n = 177), with a total of 66 patients (37.3%) with a good outcome. Among patients classified with a mismatch ≥50 mL by either the ABC/2 or planimetric method, 27–28% had a favorable outcome (Table 3). Considering only patients with age ≤80 years, the favorable outcomes were still consistent and, as expected, higher (38–39%). The ABC/2 and planimetric methods demonstrated nearly identical favorable outcome rates on the basis of the presence of positive mismatch defined as ≥50 mL.

View this table:
  • View inline
  • View popup
Table 3:

Summary of functional outcome (modified Rankin Scale) at follow-up of all patients on the basis of mismatch definition of ≥50 mL by use of the ABC/2 and planimetric methods

Inter-Rater Reliability of ABC/2 Volume Method

There was strong inter-rater correlation and agreement between the 2 independent sets of ABC/2 measurements. The Spearman correlation coefficients were 0.89, 0.91, and 0.82 for the DWI (n = 193), MTT (n = 180), and mismatch (n = 125) measurements, respectively (P < .01). The Bland-Altman plots (Fig 4) of the 2 independent ABC/2 measurements demonstrated that 95%, 95%, and 97% for the DWI, MTT, and mismatch measurements were within the thresholds defined by 2 SD from the mean differences.

Fig 4.
  • Download figure
  • Open in new tab
  • Download powerpoint
Fig 4.

Bland-Altman plots of the 2 independent ABC/2 volume measurements demonstrate the difference between the log volume of the measurements over the average for DWI (A), MTT (B), and mismatch (C). Threshold lines above and below plots represent values that are 2 SD from the mean difference. Plots are on the logarithmic scale.

Discussion

Our study demonstrates that mismatch volume calculated by the ABC/2 quantitative method is equivalent to the planimetric method. This expands on our prior study that established the equivalence between the visual and planimetric methods.5 However, as used in prior clinical trials, it is likely that a specific amount of penumbra must be calculated beyond visual confirmation of mismatch only. The equivalence between the ABC/2 and planimetric methods was supported by 3 main results. The Bland-Altman analysis demonstrated that 93% of the 193 patients in this study had mismatch volumes consistent between the ABC/2 and planimetric methods. The Spearman correlation coefficients of the DWI and MTT measurements were both high between the ABC/2 and planimetric methods. The sensitivity (0.91), specificity (0.90), accuracy (0.91), PPV (0.90), and NPV (0.91) were excellent for the ABC/2 method by use of the planimetric mismatch definition ≥50 mL. The ABC/2 method had both high PPV and NPV for the measurement of mismatch compared with the planimetric method, both of which have not been previously demonstrated in similar studies by Sims et al13 and Pedraza et al.14 This is also the largest ischemic stroke study looking at MR imaging–determined mismatch by both ABC/2 and planimetric methods. This study provides a reference for selection of mismatch thresholds and the comparability across these methods for future stroke trial design.

The ABC/2 and planimetric measurements of DWI and MTT lesion volumes used in this study are highly dependent on the “eyeball” image interpretation by the raters. The “eyeball” approach has been used and generally agreed to approximate the 20% mismatch threshold.10 In most stroke centers, this visual confirmation of mismatch is the most commonly applied method. However, the mismatch definition ≥50 mL was the focus of this study, based on the prior study5 that demonstrated equivalence between the visual method, that is, the 20% eyeball method, and the planimetric method by use of this threshold. The intrarater and inter-rater reliability of these methods have been documented as highly reliable.5,6,13 ABC/2 measurements can be performed on any scanner, and, as shown in this study and others, are a reliable and accurate method to assess brain volumes.1⇓–3,5,13 The ABC/2 has the advantage that it can be performed in real time by clinicians caring for patients with acute ischemic stroke. The average computation time of automated algorithms varies across centers; not all centers have access to automated algorithms, and not all centers acquire the images or format suitable for processing by these algorithms. If future clinical trials have inclusion criteria that are based on specific mismatch volumes, a valid, reliable, fast, and accessible method beyond visual confirmation will be required. Gómez-Mariño et al18 recommended that the ABC/2 method be applied routinely in acute stroke because it is a fast and low-cost method. We propose that the ABC/2 method is an alternative method when automated mismatch measurements are not available.

Our study has several limitations. We attempted to replicate the methods readily available on a MR imaging scanner; however, the measurements were not actually performed in an acute clinical setting. Image interpretation differences between the raters were a source for error, independent of the methods. Some of these differences probably were due to suboptimal diffusion and perfusion acquisitions compounded by the differences in the experience of the 2 raters in this study. As shown in Table 2, discrepancy case FN6 was identified as a negative perfusion case by the ABC/2 rater but was measured as a significant perfusion deficit by the planimetric rater. One specific limitation of the ABC/2 method was how discontinuous lesions were evaluated; only the largest lesion was measured rather than combining measurements across the multiple lesions. This probably contributed to some of the discrepancies seen between the ABC/2 and planimetric methods listed in Table 2.

We found that mismatch is common among thrombolytic-treated patients, whether visually confirmed (35%) or defined by mismatch ≥50 mL by use of the ABC/2 method (31%) and is associated with a favorable outcome. We conclude that the ABC/2 method is accurate for classifying the presence of MR imaging–determined quantitative mismatch in patients with acute stroke and therefore a potential tool to quickly determine a treatable mismatch pattern. One possible future study is to apply the ABC/2 method in the acute clinical setting to demonstrate the feasibility of the use of this method when making clinical trial inclusion decisions. Ideally, this study would be performed in conjunction with the application of an automated mismatch method to determine the agreement between these methods.

ACKNOWLEDGMENTS

The authors would like to acknowledge and thank the NIH Stroke Team and the patients for their valuable participation and cooperation.

Footnotes

  • This research was supported by the Division of Intramural Research of the National Institutes of Health and the National Institute of Neurological Disorders and Stroke.

Indicates open access to non-subscribers at www.ajnr.org

REFERENCES

  1. 1.↵
    1. Kothari RU,
    2. Brott T,
    3. Broderick JP,
    4. et al
    . The ABCs of measuring intracerebral hemorrhage volumes. Stroke 1996;27:1304–05
    Abstract/FREE Full Text
  2. 2.↵
    1. Gebel JM,
    2. Sila CA,
    3. Sloan MA,
    4. et al
    . Comparison of the ABC/2 estimation technique to computer-assisted volumetric analysis of intraparenchymal and subdural hematomas complicating the GUSTO-1 trial. Stroke 1998;29:1799–801
    Abstract/FREE Full Text
  3. 3.↵
    1. Huttner HB,
    2. Steiner T,
    3. Hartmann M,
    4. et al
    . Comparison of ABC/2 estimation technique to computer-assisted planimetric analysis in warfarin-related intracerebral parenchymal hemorrhage. Stroke 2006;37:404–08
    Abstract/FREE Full Text
  4. 4.↵
    1. Straka M,
    2. Albers GW,
    3. Bammer R
    . Real time diffusion-perfusion mismatch analysis in acute stroke. J Magn Reson Imaging 2010;32:1024–37
    CrossRefPubMed
  5. 5.↵
    1. Luby M,
    2. Ku KD,
    3. Latour LL,
    4. et al
    . Visual perfusion-diffusion mismatch is equivalent to quantitative mismatch. Stroke 2011;42:1010–14
    Abstract/FREE Full Text
  6. 6.↵
    1. Schellinger PD,
    2. Jansen O,
    3. Fiebach JB,
    4. et al
    . Feasibility and practicality of MR imaging of stroke in the management of hyperacute cerebral ischemia. AJNR Am J Neuroradiol 2000;21:1184–89
    Abstract/FREE Full Text
  7. 7.↵
    1. Hacke W,
    2. Albers G,
    3. Al-Rawi Y,
    4. et al.
    , DIAS Study Group. The Desmoteplase in Acute Ischemic Stroke Trial (DIAS): a phase II MRI-based 9-hour window acute stroke thrombolysis trial with intravenous desmoteplase. Stroke 2005;36:66–73
    Abstract/FREE Full Text
  8. 8.↵
    1. Furlan AJ,
    2. Eyding D,
    3. Albers GW,
    4. et al
    . Dose escalation of desmoteplase for acute ischemic stroke (DEDAS): Evidence of safety and efficacy 3 to 9 hours after stroke onset. Stroke 2006;37:1227–31
    Abstract/FREE Full Text
  9. 9.↵
    1. Hacke W,
    2. Furlan AJ,
    3. Al-Rawi Y,
    4. et al
    . Intravenous desmoteplase in patients with acute ischaemic stroke selected by MRI perfusion-diffusion weighted imaging or perfusion CT (DIAS-2): a prospective, randomised, double-blind, placebo-controlled study. Lancet Neurol 2009;8:141–50
    CrossRefPubMed
  10. 10.↵
    1. Davis SM,
    2. Donnan GA,
    3. Parsons MW,
    4. et al.
    , EPITHET Investigators. Effects of alteplase beyond 3 h after stroke in the Echoplanar Imaging Thrombolytic Evaluation Trial (EPITHET): a placebo-controlled randomised trial. Lancet Neurol 2008;7:299–309
    CrossRefPubMed
  11. 11.↵
    1. Butcher KS,
    2. Parsons M,
    3. MacGregor L,
    4. et al.
    , EPITHET Investigators. Refining the perfusion-diffusion mismatch hypothesis. Stroke 2005;36:1153–59
    Abstract/FREE Full Text
  12. 12.↵
    1. Albers GW,
    2. Thijs VN,
    3. Wechsler L,
    4. et al.
    , DEFUSE Investigators. Magnetic resonance imaging profiles predict clinical response to early reperfusion: the diffusion and perfusion imaging evaluation for understanding stroke evolution (DEFUSE) study. Ann Neurol 2006;60:508–17
    CrossRefPubMed
  13. 13.↵
    1. Sims JR,
    2. Gharai LR,
    3. Schaefer PW,
    4. et al
    . ABC/2 for rapid clinical estimate of infarct, perfusion, and mismatch volumes. Neurology 2009;72:2104–10
    CrossRef
  14. 14.↵
    1. Pedraza S,
    2. Puig J,
    3. Blasco G,
    4. et al
    . Reliability of the ABC/2 method in determining acute infarct volume. J Neuroimaging 2012;22:155–59
    CrossRefPubMed
  15. 15.↵
    1. Vogt G,
    2. Laage R,
    3. Shuaib A,
    4. et al.
    , VISTA Collaboration. Initial lesion volume is an independent predictor of clinical stroke outcome at day 90: an analysis of the Virtual International Stroke Trials Archive (VISTA) database. Stroke 2012;43:1266–72
    Abstract/FREE Full Text
  16. 16.↵
    1. Warach S,
    2. Al-Rawi Y,
    3. Furlan AJ,
    4. et al
    . Refinement of the magnetic resonance diffusion-perfusion mismatch concept for thrombolytic patient selection: insights from the desmoteplase in acute stroke trials. Stroke 2012;43:2313–18
    Abstract/FREE Full Text
  17. 17.↵
    1. Luby M,
    2. Bykowski JL,
    3. Schellinger PD,
    4. et al
    . Intra- and interrater reliability of ischemic lesion volume measurements on diffusion-weighted, mean transit time and fluid-attenuated inversion recovery MRI. Stroke 2006;37:2951–56
    Abstract/FREE Full Text
  18. 18.↵
    1. Gómez-Mariño R,
    2. André C,
    3. Novis SA
    . Volumetric determination of cerebral infarction in the acute phase using skull computed tomography without contrast: comparative study of 3 methods. Arq Neuropsiquiatr 2001;59:380–83
    PubMed
  • Received July 27, 2012.
  • Accepted after revision December 3, 2012.
  • © 2013 by American Journal of Neuroradiology
View Abstract
PreviousNext
Back to top

In this issue

American Journal of Neuroradiology: 34 (10)
American Journal of Neuroradiology
Vol. 34, Issue 10
1 Oct 2013
  • Table of Contents
  • Index by author
  • Complete Issue (PDF)
Advertisement
Print
Download PDF
Email Article

Thank you for your interest in spreading the word on American Journal of Neuroradiology.

NOTE: We only request your email address so that the person you are recommending the page to knows that you wanted them to see it, and that it is not junk mail. We do not capture any email address.

Enter multiple addresses on separate lines or separate them with commas.
Stroke Mismatch Volume with the Use of ABC/2 Is Equivalent to Planimetric Stroke Mismatch Volume
(Your Name) has sent you a message from American Journal of Neuroradiology
(Your Name) thought you would like to see the American Journal of Neuroradiology web site.
CAPTCHA
This question is for testing whether or not you are a human visitor and to prevent automated spam submissions.
Cite this article
M. Luby, J. Hong, J.G. Merino, J.K. Lynch, A.W. Hsia, A. Magadán, S.S. Song, L.L. Latour, S. Warach
Stroke Mismatch Volume with the Use of ABC/2 Is Equivalent to Planimetric Stroke Mismatch Volume
American Journal of Neuroradiology Oct 2013, 34 (10) 1901-1907; DOI: 10.3174/ajnr.A3476

Citation Manager Formats

  • BibTeX
  • Bookends
  • EasyBib
  • EndNote (tagged)
  • EndNote 8 (xml)
  • Medlars
  • Mendeley
  • Papers
  • RefWorks Tagged
  • Ref Manager
  • RIS
  • Zotero
0 Responses
Respond to this article
Share
Bookmark this article
Stroke Mismatch Volume with the Use of ABC/2 Is Equivalent to Planimetric Stroke Mismatch Volume
M. Luby, J. Hong, J.G. Merino, J.K. Lynch, A.W. Hsia, A. Magadán, S.S. Song, L.L. Latour, S. Warach
American Journal of Neuroradiology Oct 2013, 34 (10) 1901-1907; DOI: 10.3174/ajnr.A3476
del.icio.us logo Twitter logo Facebook logo Mendeley logo
  • Tweet Widget
  • Facebook Like
  • Google Plus One
Purchase

Jump to section

  • Article
    • Abstract
    • ABBREVIATIONS:
    • Materials and Methods
    • Results
    • Discussion
    • ACKNOWLEDGMENTS
    • Footnotes
    • REFERENCES
  • Figures & Data
  • Info & Metrics
  • Responses
  • References
  • PDF

Related Articles

  • No related articles found.
  • PubMed
  • Google Scholar

Cited By...

  • Use of the ABC/2 Method to Select Patients for Thrombectomy After 6 Hours of Symptom Onset
  • Adjunctive Efficacy of Intra-Arterial Conebeam CT Angiography Relative to DSA in the Diagnosis and Surgical Planning of Micro-Arteriovenous Malformations
  • Predictors of Dysphagia in Acute Pontine Infarction
  • ASPECTS (Alberta Stroke Program Early CT Score) Assessment of the Perfusion-Diffusion Mismatch
  • Crossref (25)
  • Google Scholar

This article has been cited by the following articles in journals that are participating in Crossref Cited-by Linking.

  • Neutrophil-to-Lymphocyte Ratio Predicts Cerebral Edema and Clinical Worsening Early After Reperfusion Therapy in Stroke
    Daniela Ferro, Margarida Matias, Joana Neto, Rafael Dias, Goreti Moreira, Nils Petersen, Elsa Azevedo, Pedro Castro
    Stroke 2021 52 3
  • Predictors of Dysphagia in Acute Pontine Infarction
    Sriramya Lapa, Sebastian Luger, Waltraud Pfeilschifter, Christian Henke, Marlies Wagner, Christian Foerch
    Stroke 2017 48 5
  • ASPECTS (Alberta Stroke Program Early CT Score) Assessment of the Perfusion–Diffusion Mismatch
    Louis Lassalle, Guillaume Turc, Marie Tisserand, Sylvain Charron, Pauline Roca, Stephanie Lion, Laurence Legrand, Myriam Edjlali, Olivier Naggara, Jean-François Meder, Jean-Louis Mas, Jean-Claude Baron, Catherine Oppenheim
    Stroke 2016 47 10
  • Prognostic factors for long-term improvement from stroke-related aphasia with adequate linguistic rehabilitation
    Yoshitaka Nakagawa, Yoko Sano, Michitaka Funayama, Masahiro Kato
    Neurological Sciences 2019 40 10
  • Clinical and Radiological Predictors of Malignant Middle Cerebral Artery Infarction Development and Outcomes
    Angelique F. Albert, Matthew A. Kirkman
    Journal of Stroke and Cerebrovascular Diseases 2017 26 11
  • Recanalization Treatments for Pediatric Acute Ischemic Stroke in France
    Manoëlle Kossorotoff, Basile Kerleroux, Grégoire Boulouis, Béatrice Husson, Kim Tran Dong, François Eugene, Lena Damaj, Augustin Ozanne, Céline Bellesme, Anne Rolland, Romain Bourcier, Aude Triquenot-Bagan, Gaultier Marnat, Jean-Philippe Neau, Sylvie Joriot, Alexandra Perez, Maud Guillen, Maximilien Perivier, Frederique Audic, Jean François Hak, Christian Denier, Olivier Naggara, WAGIH BEN HASSEN, MANOËLLE KOSSOROTOFF, OLIVIER NAGGARA, BASILE KERLEROUX, CHRISTIAN DENIER, AUGUSTIN OZANNE, CÉLINE BELLESME, BÉATRICE HUSSON, CHABRIAT HUGUES, REINER PEGGY, CATHERINE LAMY, FREDERIC CLARENÇON, SANDRINE DELTOUR, MICHÈLE LEVASSEUR, FRANÇOIS LUN, HASSAN HOSSEINI, ADRIEN VILLAIN, CHANTAL LAMY, LOÏC HERY, CYRIL CHIVOT, SOPHIE GUEDEN, BENJAMIN BOUAMRA, JOANNA BELLEVILLE GOFFENEY, ALESSANDRA BIONDI, PAULINE RENOU, MARIE THIBAUD, GAULTIER MARNAT, NATHALIE BACH, ANNA FERRIER, GANAELLE REMERAND, EMMANUEL CHABERT, YANNICK BÉJOT, OLIVIER DETANTE, ELODIE LAMETERY, FLORENCE TAHON, CHARLOTTE CORDONNIER, JORIOT SYLVIE, KAZEMI APOLLINE, CECILE LAROCHE, SUZANA SALEME, LAURENT DEREX, MARYLINE CARNEIRO, OMER EKER, FREDERIQUE AUDIC, PHILIPPE DORY LAUTREC, NADINE GIRARD, CAROLINE ARQUIZAN, PIERRE MEYER, SEBASTIEN RICHARD, CLAIRE BILBAULT, HUBERT DESAL, ANNE ROLLAND, BOURCIER ROMAIN, EMMANUELLE GONDON, JACQUES SEDAT, PASCAL AUZOU, CANAN OZSANCAK, GUILLAUME CAMI, JEAN PHILIPPE NEAU, NICOLAS RAYNAUD, STÉPHANE VELASCO, STEPHANE VANNIER, LÉNA DAMAJ, JEAN CHRISOPHE FERRÉ, FRANCOIS EUGENE, AUDE TRIQUENOT BAGAN, CHRISANTHI PAPAGIANNAKI, VALÉRIE WOLFF, ALEXANDRA PEREZ, RÉMY BEAUJEUX, EMMANUEL CHEURET, JEAN DARCOURT, KEVIN JANOT, MAXIMILIEN PERIVIER, DENIS HERBRETEAUX
    JAMA Network Open 2022 5 9
  • Statistical textural feature and deformable model based brain tumor segmentation and volume estimation
    Shoaib Amin Banday, Ajaz Hussain Mir
    Multimedia Tools and Applications 2017 76 3
  • Penumbra quantification from MR SWI‐DWI mismatch and its comparison with MR ASL PWI‐DWI mismatch in patients with acute ischemic stroke
    Rupsa Bhattacharjee, Rakesh Kumar Gupta, Biplab Das, Vijay Kant Dixit, Praveen Gupta, Anup Singh
    NMR in Biomedicine 2021 34 7
  • Cerebral Blood Flow Response During Bolus Normal Saline Infusion After Ischemic Stroke
    Michael T. Mullen, Ashwin B. Parthasarathy, Ali Zandieh, Wesley B. Baker, Rickson C. Mesquita, Caitlin Loomis, Jose Torres, Wensheng Guo, Christopher G. Favilla, Steven R. Messé, Arjun G. Yodh, John A. Detre, Scott E. Kasner
    Journal of Stroke and Cerebrovascular Diseases 2019 28 11
  • Cerebral embolic protection and severity of stroke following transcatheter aortic valve replacement
    Toshiaki Isogai, Husitha Reddy Vanguru, Amar Krishnaswamy, Ankit Agrawal, Nikolaos Spilias, Shashank Shekhar, Anas M. Saad, Beni Rai Verma, Rishi Puri, Grant W. Reed, Zoran B. Popović, Shinya Unai, James J. Yun, Ken Uchino, Samir R. Kapadia
    Catheterization and Cardiovascular Interventions 2022 100 5

More in this TOC Section

  • Usefulness of Quantitative Susceptibility Mapping for the Diagnosis of Parkinson Disease
  • White Matter Alterations in the Brains of Patients with Active, Remitted, and Cured Cushing Syndrome: A DTI Study
  • Qualitative and Quantitative Analysis of MR Imaging Findings in Patients with Middle Cerebral Artery Stroke Implanted with Mesenchymal Stem Cells
Show more BRAIN

Similar Articles

Advertisement

Indexed Content

  • Current Issue
  • Accepted Manuscripts
  • Article Preview
  • Past Issues
  • Editorials
  • Editor's Choice
  • Fellows' Journal Club
  • Letters to the Editor
  • Video Articles

Cases

  • Case Collection
  • Archive - Case of the Week
  • Archive - Case of the Month
  • Archive - Classic Case

Special Collections

  • AJNR Awards
  • ASNR Foundation Special Collection
  • Most Impactful AJNR Articles
  • Photon-Counting CT
  • Spinal CSF Leak Articles (Jan 2020-June 2024)

More from AJNR

  • Trainee Corner
  • Imaging Protocols
  • MRI Safety Corner

Multimedia

  • AJNR Podcasts
  • AJNR Scantastics

Resources

  • Turnaround Time
  • Submit a Manuscript
  • Submit a Video Article
  • Submit an eLetter to the Editor/Response
  • Manuscript Submission Guidelines
  • Statistical Tips
  • Fast Publishing of Accepted Manuscripts
  • Graphical Abstract Preparation
  • Imaging Protocol Submission
  • Evidence-Based Medicine Level Guide
  • Publishing Checklists
  • Author Policies
  • Become a Reviewer/Academy of Reviewers
  • News and Updates

About Us

  • About AJNR
  • Editorial Board
  • Editorial Board Alumni
  • Alerts
  • Permissions
  • Not an AJNR Subscriber? Join Now
  • Advertise with Us
  • Librarian Resources
  • Feedback
  • Terms and Conditions
  • AJNR Editorial Board Alumni

American Society of Neuroradiology

  • Not an ASNR Member? Join Now

© 2025 by the American Society of Neuroradiology All rights, including for text and data mining, AI training, and similar technologies, are reserved.
Print ISSN: 0195-6108 Online ISSN: 1936-959X

Powered by HighWire