IB Diffusion

MRI diffusion weighted imaging processing.

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Diffusion

Overview

To assess tumor response to treatment, radiologists have to make two-dimensional measurements on contrast-enhanced MRI (CE-MRI) which may not reflect true changes in tumor growth. Moreover, radiation necrosis may mimic true tumor on CE-MRI, further confounding treatment decisions. 

IB Diffusion is an advanced image post-processing solution that accepts commonly acquired diffusion weighted imaging (DWI) and outputs an array of parameter maps including apparent diffusion coefficient (ADC), extrapolated b-value DWI, intravoxel incoherent motion (IVIM), and stretched exponential parameters, alpha (α) and distributed diffusion coefficient (DDC). 

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Features

  • The IB Diffusion module performs post-processing of MR diffusion-weighted images (DWI) to determine diffusion-related parameters.
  • Using standard algorithms, it generates parametric images such as Apparent Diffusion Coefficient (ADC).

Benefits

  • One of Imaging Biometrics’ clients is using IB Diffusion extrapolated b-value ADC to aid in the assessment of prostate MRI exams on 1.5T scanners. The extrapolate b-value maps make the lesion “pop” on MRI images. While this capability (higher b-values) is available on 3T scanners, the software’s ability to generate extrapolated b-values on 1.5T is of value. In this way, IB Diffusion can help the healthcare organisation get more out of existing MRI scanners and exams. 
  • A 2019 “diffusion challenge” by the National Cancer Institute Quantitative Imaging Network identified IB Diffusion to be highly robust as compared to other diffusion weighted imaging (DWI) algorithms.¹

Image examples

IB-Diffusion-ADC
IB-Diffusion-DDC

To find out more about this solution or any of the other 140+ applications on the Blackford Platform, please book a discovery call with our team.

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¹LaViolette PS, McGarry SD, Bukowy JD, Lowman AK, Banerjee A, Malyarenko D, et al. Multi-site concordance of diffusion weighted imaging derived metrics, a comparison of fitting algorithms for differentiating whole-mount, pathologically confirmed, prostate cancer of differing Gleason patterns. Ismrm.org. 2016 [cited 2023 Jul 19]. Available from: https://cds.ismrm.org/protected/19MProceedings/PDFfiles/3598.html