title: Characterization of cervical lymph-nodes using a multi-parametric and multi-modal approach for an early prediction of tumor response to chemo-radiotherapy.
abstract: OBJECTIVE
  In the treatment of Head-and-Neck Squamous Cell Carcinoma (HNSCC), the early prediction of residual malignant lymph nodes (LNs) is currently required. Here, we investigated the potential of a multi-modal characterization (combination of CT, T2w-MRI and DW-MRI) at baseline and at mid-treatment, based on texture analysis (TA), for the early prediction of LNs response to chemo-radiotherapy (CRT).
  
  
  METHODS
  30 patients with pathologically confirmed HNSCC treated with CRT were considered. All patients underwent a planning CT and two serial MR examinations (including T2w and DW images), one before and one at mid-CRT. For each patient the largest malignant LN was selected and within each LN, morphological and textural features were estimated from T2w-MRI and CT, besides a quantification of the apparent diffusion coefficient (ADC) from DW-MRI. After a median follow-up time of 26.6months, 19 LNs showed regional control, while 11 LNs showedregional failure at a median time of 4.6months. Linear discriminant analysis was used to test the accuracy of the image-based features in predicting the final response.
  
  
  RESULTS
  Pre-treatment features showed higher predictive power than mid-CRT features, the ADC having the highest accuracy (80%); CT-based indices were found not predictive. When ADC was combined with TA, the classification performance increased (accuracy=82.8%). If only T2w-MRI features were considered, the best combination of pre-CRT indices and their variation reached an equivalent accuracy (81.8%).
  
  
  CONCLUSIONS
  Our results may suggest that TA on T2w-MRI and ADC can be combined together to obtain a more accurate prediction of response to CRT.
authors.affiliation: Institute of Molecular Bioimaging and Physiology (IBFM), CNR, Segrate (MI), Italy. Electronic address: elisa.scalco@ibfm.cnr.it.
authors.forename: Elisa
authors.initials: E
authors.lastname: Scalco
authors.affiliation: Medical Physics Laboratory, Regina Elena National Cancer Institute, Rome, Italy.
authors.forename: Simona
authors.initials: S
authors.lastname: Marzi
authors.affiliation: Department of Radiotherapy, Regina Elena National Cancer Institute, Rome, Italy.
authors.forename: Giuseppe
authors.initials: G
authors.lastname: Sanguineti
authors.affiliation: Radiology and Diagnostic Imaging Department, Regina Elena National Cancer Institute, Rome, Italy.
authors.forename: Antonello
authors.initials: A
authors.lastname: Vidiri
authors.affiliation: Institute of Molecular Bioimaging and Physiology (IBFM), CNR, Segrate (MI), Italy.
authors.forename: Giovanna
authors.initials: G
authors.lastname: Rizzo
mesh_terms: D000328:Adult; D000368:Aged; D000369:Aged, 80 and over; D002294:Carcinoma, Squamous Cell / Q000000981:diagnostic imaging / Q000473:pathology* / Q000628:therapy*; D059248:Chemoradiotherapy; D016002:Discriminant Analysis; D005260:Female; D006258:Head and Neck Neoplasms / Q000000981:diagnostic imaging / Q000473:pathology* / Q000628:therapy*; D006801:Humans; D016014:Linear Models; D008198:Lymph Nodes / Q000000981:diagnostic imaging* / Q000473:pathology; D008207:Lymphatic Metastasis; D008279:Magnetic Resonance Imaging; D008297:Male; D008875:Middle Aged; D015233:Models, Statistical; D064847:Multimodal Imaging; D014057:Tomography, X-Ray Computed; D016896:Treatment Outcome
keywords: DW-MRI; Head-and-neck lymph-nodes; T2w-MRI; Texture analysis