A method to analyze the evolution of malignant gliomas using MRI

Maria Ida Iacono, Katia Passera, Lorenzo Magrassi, Luca Mainardi, Stefano Bastianello, Paolo Lago

Research output: Contribution to journalArticlepeer-review


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.

Original languageEnglish
Pages (from-to)571-579
Number of pages9
JournalInternational journal of computer assisted radiology and surgery
Issue number6
Publication statusPublished - 2008


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

ASJC Scopus subject areas

  • Radiology Nuclear Medicine and imaging
  • Health Informatics
  • Surgery
  • Transplantation


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