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A method to analyze the evolution of malignant gliomas using MRI

  • Maria Ida Iacono
  • Katia Passera
  • Lorenzo Magrassi
  • Luca Mainardi
  • Stefano Bastianello
  • Paolo Lago
Original Article

Abstract

Objective

To introduce a novel approach for the monitoring of glioma evolution by the extraction of mathematical parameters from follow-up MRI.

Material and methods

The method consists of the registration of follow-up MR images and the analysis of the deformation field. The registration was performed through an affine transformation followed by a non-rigid registration using free-form deformations (FFDs). A subsequent analysis of the transformation non-linear component is then performed by using the jacobian operator in order to extract information related to tumor evolution. In order to test the algorithm’s performance two different validations were performed: (a) a numerical validation utilizing both physical and digital phantoms, (b) a clinical validation using neurosurgeon clinical judgements.

Results

Quantitative validation showed that the jacobian describes the volumetric variations of the physical phantom with an error of 5%. Furthermore, simulations with a digital phantom provided an estimation of the error introduced by registration (6.4%). Clinical validation provided good clinical scores: the score evaluating the correspondence between extracted variables and patient evolution was 4.37  ±  0.89 for the deformation field and 4.43  ±  0.82 for the jacobian image (top score: 5).

Conclusion

The novel approach leads to an objective and quantitative description of tumor evolution. Therefore, it could be valuable for planning interventions and/or treatments.

Keywords

Computer-assisted image processing Deformation field Jacobian operator Follow-up studies 

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Copyright information

© CARS 2008

Authors and Affiliations

  • Maria Ida Iacono
    • 1
  • Katia Passera
    • 1
  • Lorenzo Magrassi
    • 2
  • Luca Mainardi
    • 1
  • Stefano Bastianello
    • 3
  • Paolo Lago
    • 4
  1. 1.Biomedical Engineering DepartmentPolitecnico di MilanoMilanItaly
  2. 2.Neurosurgery Division, Department of SurgeryIRCCS S. Matteo, University of PaviaPaviaItaly
  3. 3.Department of NeuroradiologyIRCCS MondinoPaviaItaly
  4. 4.Clinical Engineering DepartmentIRCCS S. MatteoPaviaItaly

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