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Digital archive of theses discussed at the University of Pisa

 

Thesis etd-04302018-211902


Thesis type
Tesi di laurea specialistica LC6
Author
MARCIANO, ANDREA
URN
etd-04302018-211902
Thesis title
Advanced texture analysis of [18F]FMCH intratumor heterogeneity in patients with prostate cancer recurrence
Department
RICERCA TRASLAZIONALE E DELLE NUOVE TECNOLOGIE IN MEDICINA E CHIRURGIA
Course of study
MEDICINA E CHIRURGIA
Supervisors
relatore Prof.ssa Erba, Paola Anna
Keywords
  • multimodality imaging
  • PET/CT
  • prostate cancer
  • radiomic
  • texture analysis
Graduation session start date
15/05/2018
Availability
Withheld
Release date
15/05/2088
Summary
The aim of this work is to evaluate texture analysis in patients with biochemical recurrence of PCa after primary therapy studied with [18F]FECH PET/CT. Methods: Between Jan 2011 and Dec 2017 we prospectively evaluated a series of 82 patients with recurrent PCa. Patients were classified by Gleason Score , by the presence of an ongoing therapy (Hormone-therapy) and based on [18F]FECH PET/CT results on Oligometastatic or Multimetastatic disease. A total of 339 lesions were found and they were further classified based on the site of disease relapse based on TNM classification. Images were segmented with a semiautomatic method and the texture analysis was performed using a dedicated software. Results: Texture features analysis allowed to highlight the heterogeneity of the lesions, managing to differentiate the bone lesions from the lymph nodes, and between distant lymph node lesions from the regional ones. A group of seven features proved to be able to differentiate lesions on the basis of the Gleason score and also on the basis of Oligo or Multimetastatic status. About 60% (35/58) of the features positive correlation results non-dependent from ongoing therapy. Conclusions: [18F]Cho PET/CT texture analysis proved to be able to characterize the heterogeneity of lesions in the prostate cancer better than the only semi-quantitative indexes. Texture features analysis seems to be a valid tool and candidates itself to be added to the other biomarker (Gleason Score) to make the staging of the disease more reliable and allocate it to the most appropriate treatment.
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