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Tumour functional sphericity from PET images: prognostic value in NSCLC and impact of delineation method.

Mathieu HattBaptiste LaurentHadi FayadVincent JaouenDimitris VisvikisCatherine Cheze Le Rest
Published in: European journal of nuclear medicine and molecular imaging (2017)
Tumour functional sphericity was found to be dependent on the segmentation method, although the accuracy in retrieving the true sphericity was not dependent on tumour volume. In addition, even accurate segmentation can lead to an inaccurate sphericity value, and vice versa. Sphericity had similar or lower prognostic value than volume alone in the patients with lung cancer, except when determined using the FLAB method for which there was a small improvement in stratification when the parameters were combined.
Keyphrases
  • deep learning
  • convolutional neural network
  • small cell lung cancer
  • computed tomography
  • pet ct
  • advanced non small cell lung cancer
  • epidermal growth factor receptor
  • tyrosine kinase
  • brain metastases