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MRI perfusion analysis using freeware, standard imaging software.

ABSTRACT: BACKGROUND:Perfusion-weighted imaging is only scarcely used in veterinary medicine. The exact reasons are unclear. One reason might be the typically high costs of the software packages for image analysis. In addition, a great variability concerning available programs makes it hard to compare results between different studies. Moreover, these algorithms are tuned for their usage in human medicine and often difficult to adapt to veterinary studies. In order to address these issues, our aim is to deliver a free open source package for calculating quantitative perfusion parameters. We develop an "R package" calculating mean transit time, cerebral blood flow and cerebral blood volume from data obtained with freely imaging software (OsiriX Light®). We hope that the free availability, in combination with the fact that the underlying algorithm is open and adaptable, makes it easier for scientists in veterinary medicine to use, compare and adapt perfusion-weighted imaging analysis. In order to demonstrate the usage of our software package, we reviewed previously acquired perfusion-weighted images from a group of eight purpose-breed healthy beagle dogs and twelve client-owned dogs with idiopathic epilepsy. In order to obtain the data needed for our algorithm, the following steps were performed: First, regions of interest (ROI) were drawn around different, previously reported, brain regions and the middle cerebral artery. Second, a ROI enhancement curve was generated for each ROI using a freely available PlugIn. Third, the signal intensity curves were exported as a comma-separated-value file. These files constitute the input to our software package, which then calculates the PWI parameters. RESULTS:We used our software package to re-assess perfusion weighted images from two previous studies. The clinical results were similar, showing a significant increase in the mean transit time and a significant decrease in cerebral blood flow for diseased dogs. CONCLUSION:We provide an "R package" for computing the main perfusion parameters from measurements taken with standard imaging software and describe in detail how to obtain these measurements. We hope that our contribution enables users in veterinary medicine to easily obtain perfusion parameters using standard Open Source software in a standard, adaptable and comparable way.

SUBMITTER: Hartmann A

PROVIDER: S-EPMC7236203 | biostudies-literature | 2020 May

REPOSITORIES: biostudies-literature

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MRI perfusion analysis using freeware, standard imaging software.

Hartmann Antje A Scholz Volkher B VB Lautenschläger Ines E IE

BMC veterinary research 20200518 1

<h4>Background</h4>Perfusion-weighted imaging is only scarcely used in veterinary medicine. The exact reasons are unclear. One reason might be the typically high costs of the software packages for image analysis. In addition, a great variability concerning available programs makes it hard to compare results between different studies. Moreover, these algorithms are tuned for their usage in human medicine and often difficult to adapt to veterinary studies. In order to address these issues, our aim ...[more]

PMID: 32423403

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Project description:Background and purposeRelative cerebral blood volume, as measured by T2*-weighted dynamic susceptibility-weighted contrast-enhanced MRI, represents the most robust and widely used perfusion MR imaging metric in neuro-oncology. Our aim was to determine whether differences in modeling implementation will impact the correction of leakage effects (from blood-brain barrier disruption) and the accuracy of relative CBV calculations as measured on T2*-weighted dynamic susceptibility-weighted contrast-enhanced MR imaging at 3T field strength.Materials and methodsThis study included 52 patients with glioma undergoing DSC MR imaging. Thirty-six patients underwent both non-preload dose- and preload dose-corrected DSC acquisitions, with 16 patients undergoing preload dose-corrected acquisitions only. For each acquisition, we generated 2 sets of relative CBV metrics by using 2 separate, widely published, FDA-approved commercial software packages: IB Neuro and nordicICE. We calculated 4 relative CBV metrics within tumor volumes: mean relative CBV, mode relative CBV, percentage of voxels with relative CBV > 1.75, and percentage of voxels with relative CBV > 1.0 (fractional tumor burden). We determined Pearson (r) and Spearman (ρ) correlations between non-preload dose- and preload dose-corrected metrics. In a subset of patients with recurrent glioblastoma (n = 25), we determined receiver operating characteristic area under the curve for fractional tumor burden accuracy to predict the tissue diagnosis of tumor recurrence versus posttreatment effect. We also determined correlations between rCBV and microvessel area from stereotactic biopsies (n = 29) in 12 patients.ResultsWith IB Neuro, relative CBV metrics correlated highly between non-preload dose- and preload dose-corrected conditions for fractional tumor burden (r = 0.96, ρ = 0.94), percentage > 1.75 (r = 0.93, ρ = 0.91), mean (r = 0.87, ρ = 0.86), and mode (r = 0.78, ρ = 0.76). These correlations dropped substantially with nordicICE. With fractional tumor burden, IB Neuro was more accurate than nordicICE in diagnosing tumor versus posttreatment effect (area under the curve = 0.85 versus 0.67) (P < .01). The highest relative CBV-microvessel area correlations required preload dose and IB Neuro (r = 0.64, ρ = 0.58, P = .001).ConclusionsDifferent implementations of perfusion MR imaging software modeling can impact the accuracy of leakage correction, relative CBV calculation, and correlations with histologic benchmarks.

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Project description:IntroductionComputed tomography perfusion (CTP) imaging has become an important tool in evaluating acute recanalization treatment candidates. Large clinical trials have successfully used RAPID automated imaging analysis software for quantifying ischemic core and penumbra, yet other commercially available software vendors are also on the market. We evaluated the possible difference in ischemic core and perfusion lesion volumes and the agreement rate of target mismatch between OLEA, MIStar, and Syngo.Via versus RAPID software in acute recanalization treatment candidates.Patients and methodsAll consecutive stroke-code patients with baseline CTP RAPID imaging at Helsinki University Hospital during 8/2018-9/2021 were included. Ischemic core was defined as cerebral blood flow <30% than the contralateral hemisphere and within the area of delay time (DT) >3s with MIStar. Perfusion lesion volume was defined as DT > 3 s (MIStar) and Tmax > 6 s with all other software. A perfusion mismatch ratio of ⩾1.8, a perfusion lesion volume of ⩾15 mL, and ischemic core <70 mL was defined as target mismatch. The mean pairwise differences of the core and perfusion lesion volumes between software were calculated using the Bland-Altman method and the agreement of target mismatch between software using the Pearson correlation.ResultsA total of 1606 patients had RAPID perfusion maps, 1222 of which had MIStar, 596 patients had OLEA, and 349 patients had Syngo.Via perfusion maps available. Each software was compared with simultaneously analyzed RAPID software. MIStar showed the smallest core difference compared with RAPID (-2 mL, confidence interval (CI) from -26 to 22), followed by OLEA (2 mL, CI from -33 to 38). Perfusion lesion volume differed least with MIStar (4 mL, CI from -62 to 71) in comparison with RAPID, followed by Syngo.Via (6 mL, CI from -94 to 106). MIStar had the best agreement rate with target mismatch of RAPID followed by OLEA and Syngo.Via.Discussion and conclusionComparison of RAPID with three other automated imaging analysis software showed variance in ischemic core and perfusion lesion volumes and in target mismatch.

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MRI perfusion analysis using freeware, standard imaging software.

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MRI perfusion analysis using freeware, standard imaging software.

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