title: Characterizing Heterogeneity within Head and Neck Lesions Using Cluster Analysis of Multi-Parametric MRI Data.
abstract: OBJECTIVE
  To describe a methodology, based on cluster analysis, to partition multi-parametric functional imaging data into groups (or clusters) of similar functional characteristics, with the aim of characterizing functional heterogeneity within head and neck tumour volumes. To evaluate the performance of the proposed approach on a set of longitudinal MRI data, analysing the evolution of the obtained sub-sets with treatment.
  
  
  METHODS
  The cluster analysis workflow was applied to a combination of dynamic contrast-enhanced and diffusion-weighted imaging MRI data from a cohort of squamous cell carcinoma of the head and neck patients. Cumulative distributions of voxels, containing pre and post-treatment data and including both primary tumours and lymph nodes, were partitioned into k clusters (k = 2, 3 or 4). Principal component analysis and cluster validation were employed to investigate data composition and to independently determine the optimal number of clusters. The evolution of the resulting sub-regions with induction chemotherapy treatment was assessed relative to the number of clusters.
  
  
  RESULTS
  The clustering algorithm was able to separate clusters which significantly reduced in voxel number following induction chemotherapy from clusters with a non-significant reduction. Partitioning with the optimal number of clusters (k = 4), determined with cluster validation, produced the best separation between reducing and non-reducing clusters.
  
  
  CONCLUSIONS
  The proposed methodology was able to identify tumour sub-regions with distinct functional properties, independently separating clusters which were affected differently by treatment. This work demonstrates that unsupervised cluster analysis, with no prior knowledge of the data, can be employed to provide a multi-parametric characterization of functional heterogeneity within tumour volumes.
authors.affiliation: CR-UK Cancer Imaging Centre, The Royal Marsden NHS Foundation Trust and The Institute of Cancer Research, London, United Kingdom.
authors.forename: Marco
authors.initials: M
authors.lastname: Borri
authors.affiliation: CR-UK Cancer Imaging Centre, The Royal Marsden NHS Foundation Trust and The Institute of Cancer Research, London, United Kingdom.
authors.forename: Maria A
authors.initials: MA
authors.lastname: Schmidt
authors.affiliation: Head and Neck Unit, The Royal Marsden NHS Foundation Trust, London, United Kingdom.
authors.forename: Ceri
authors.initials: C
authors.lastname: Powell
authors.affiliation: CR-UK Cancer Imaging Centre, The Royal Marsden NHS Foundation Trust and The Institute of Cancer Research, London, United Kingdom; Radiology Department, The Royal Marsden NHS Foundation Trust, London, United Kingdom.
authors.forename: Dow-Mu
authors.initials: DM
authors.lastname: Koh
authors.affiliation: Radiology Department, The Royal Marsden NHS Foundation Trust, London, United Kingdom.
authors.forename: Angela M
authors.initials: AM
authors.lastname: Riddell
authors.affiliation: CRUK/MRC Oxford Institute for Radiation Oncology, University of Oxford, Oxford, United Kingdom.
authors.forename: Mike
authors.initials: M
authors.lastname: Partridge
authors.affiliation: Head and Neck Unit, The Royal Marsden NHS Foundation Trust, London, United Kingdom.
authors.forename: Shreerang A
authors.initials: SA
authors.lastname: Bhide
authors.affiliation: Head and Neck Unit, The Royal Marsden NHS Foundation Trust, London, United Kingdom.
authors.forename: Christopher M
authors.initials: CM
authors.lastname: Nutting
authors.affiliation: Head and Neck Unit, The Royal Marsden NHS Foundation Trust, London, United Kingdom.
authors.forename: Kevin J
authors.initials: KJ
authors.lastname: Harrington
authors.affiliation: Head and Neck Unit, The Royal Marsden NHS Foundation Trust, London, United Kingdom.
authors.forename: Katie L
authors.initials: KL
authors.lastname: Newbold
authors.affiliation: CR-UK Cancer Imaging Centre, The Royal Marsden NHS Foundation Trust and The Institute of Cancer Research, London, United Kingdom.
authors.forename: Martin O
authors.initials: MO
authors.lastname: Leach
mesh_terms: D000465:Algorithms; D002294:Carcinoma, Squamous Cell / Q000473:pathology; D016000:Cluster Analysis; D038524:Diffusion Magnetic Resonance Imaging / Q000379:methods; D006257:Head / Q000473:pathology*; D006258:Head and Neck Neoplasms / Q000473:pathology*; D006801:Humans; D008137:Longitudinal Studies; D008198:Lymph Nodes / Q000473:pathology; D009333:Neck / Q000473:pathology*; D025341:Principal Component Analysis / Q000379:methods; D011446:Prospective Studies