title: Texture analysis as imaging biomarker of tumoral response to neoadjuvant chemoradiotherapy in rectal cancer patients studied with 3-T magnetic resonance.
abstract: OBJECTIVE
  The aim of this study was to determine whether texture features of rectal cancer on T2-weighted (T2w) magnetic resonance images can predict tumoral response in patients treated with neoadjuvant chemoradiotherapy (CRT).
  
  
  METHODS
  We prospectively enrolled 15 consecutive patients (6 women, 63.2 ± 13.4 years) with rectal cancer, who underwent pretreatment and midtreatment 3-T magnetic resonance imaging. Treatment protocol consisted of neoadjuvant CRT with oxaliplatin and 5-fluorouracile. Texture analysis using a filtration-histogram technique was performed using a commercial research software algorithm (TexRAD Ltd, Somerset, England, United Kingdom) on unenhanced axial T2w images by manually delineating a region of interest around the tumor outline for the largest cross-sectional area. The technique selectively filters and extracts textures at different anatomic scales followed by quantification of the histogram using kurtosis, entropy, skewness, and mean value of positive pixels. After CRT, all patients underwent complete surgical resection and the surgical specimen served as the gold standard.
  
  
  RESULTS
  Six patients showed pathological complete response (pCR), and 4 patients, partial response (PR). Five patients were classified as nonresponders (NRs). Pretreatment medium texture-scale quantified as kurtosis was significantly lower in the pCR subgroup in comparison with the PR + NR subgroup (P = 0.01). Midtreatment kurtosis without filtration was significantly higher in pCR in comparison with PR + NR (P = 0.045). The change in kurtosis between midtreatment and pretreatment images was significantly lower in the PR + NR subgroup compared with the pCR subgroup (P = 0.038). Pretreatment area under the receiver operating characteristic curves, to discriminate between pCR and PR + NR, was significantly higher for kurtosis (0.907, P < 0.001) compared with all other parameters. The optimal cutoff value for pretreatment kurtosis was 0.19 or less. Using this value, the sensitivity and specificity for pCR prediction were 100% and 77.8%, respectively.
  
  
  CONCLUSIONS
  Texture parameters derived from T2w images of rectal cancer have the potential to act as imaging biomarkers of tumoral response to neoadjuvant CRT.
authors.affiliation: From the *Department of Radiological Sciences, Oncology, and Pathology, University of Rome "Sapienza"-Polo Pontino, Latina, Italy; †Department of Radiology and Radiological Science, Medical University of South Carolina, Charleston; ‡Clinical Imaging Sciences Centre, Brighton and Sussex Medical School, Falmer, Sussex, England; §Institute for Clinical Radiology, Ludwig-Maximilians-University Hospital, Munich, Germany; and ∥Department of Radiotherapy, University of Rome "Sapienza", Rome, Italy.
authors.forename: Carlo N
authors.initials: CN
authors.lastname: De Cecco
authors.forename: Balaji
authors.initials: B
authors.lastname: Ganeshan
authors.forename: Maria
authors.initials: M
authors.lastname: Ciolina
authors.forename: Marco
authors.initials: M
authors.lastname: Rengo
authors.forename: Felix G
authors.initials: FG
authors.lastname: Meinel
authors.forename: Daniela
authors.initials: D
authors.lastname: Musio
authors.forename: Francesca
authors.initials: F
authors.lastname: De Felice
authors.forename: Nicola
authors.initials: N
authors.lastname: Raffetto
authors.forename: Vincenzo
authors.initials: V
authors.lastname: Tombolini
authors.forename: Andrea
authors.initials: A
authors.lastname: Laghi
mesh_terms: D014408:Biomarkers, Tumor; D059248:Chemoradiotherapy / Q000379:methods*; D005260:Female; D006801:Humans; D008279:Magnetic Resonance Imaging / Q000379:methods*; D008297:Male; D008875:Middle Aged; D020360:Neoadjuvant Therapy / Q000379:methods*; D011446:Prospective Studies; D012372:ROC Curve; D012004:Rectal Neoplasms / Q000628:therapy*; D012680:Sensitivity and Specificity; D016896:Treatment Outcome
chemical_list: D014408:Biomarkers, Tumor