title: Combined PET/CT image characteristics for radiotherapy tumor response in lung cancer.
abstract: OBJECTIVE
  Prediction of local failure in radiotherapy patients with non-small cell lung cancer (NSCLC) remains a challenging task. Recent evidence suggests that FDG-PET images can be used to predict outcomes. We investigate an alternative multimodality image-feature approach for predicting post-radiotherapy tumor progression in NSCLC.
  
  
  METHODS
  We analyzed pre-treatment FDG-PET/CT studies of twenty-seven NSCLC patients for local and loco-regional failures. Thirty-two tumor region features based on SUV or HU, intensity-volume-histogram (IVH) and texture characteristics were extracted. Statistical analysis was performed using Spearman's correlation (rs) and multivariable logistic regression.
  
  
  RESULTS
  For loco-regional recurrence, IVH variables had the highest univariate association. In PET, IVH-slope reached rs=0.3426 (p=0.0403). Motion correction slightly improved correlation of texture features. In CT, coefficient of variation had the highest association rs=-0.2665 (p=0.0871). Similarly for local failure, a CT-IVH parameter reached rs=0.4530 (p=0.0105). For loco-regional and local failures, a 2-parameter model of PET-V(80) and CT-V(70) yielded rs=0.4854 (p=0.0067) and rs=0.5908 (p=0.0013), respectively. Addition of dosimetric variables provided improvement in cases of loco-regional but not local failures.
  
  
  CONCLUSIONS
  We proposed a feature-based approach to evaluate radiation tumor response. Our study demonstrates that multimodality image-feature modeling provides better performance compared to existing metrics and holds promise for individualizing radiotherapy planning.
authors.affiliation: Washington University, Saint Louis, MO, USA.
authors.forename: Manushka
authors.initials: M
authors.lastname: Vaidya
authors.forename: Kimberly M
authors.initials: KM
authors.lastname: Creach
authors.forename: Jennifer
authors.initials: J
authors.lastname: Frye
authors.forename: Farrokh
authors.initials: F
authors.lastname: Dehdashti
authors.forename: Jeffrey D
authors.initials: JD
authors.lastname: Bradley
authors.forename: Issam
authors.initials: I
authors.lastname: El Naqa
mesh_terms: D000368:Aged; D000369:Aged, 80 and over; D002289:Carcinoma, Non-Small-Cell Lung / Q000000981:diagnostic imaging* / Q000473:pathology / Q000532:radiotherapy*; D018450:Disease Progression; D005260:Female; D006801:Humans; D008175:Lung Neoplasms / Q000000981:diagnostic imaging* / Q000473:pathology / Q000532:radiotherapy*; D008297:Male; D008875:Middle Aged; D015233:Models, Statistical; D064847:Multimodal Imaging; D009367:Neoplasm Staging; D010363:Pattern Recognition, Automated; D049268:Positron-Emission Tomography; D011237:Predictive Value of Tests; D011829:Radiation Dosage; D012189:Retrospective Studies; D014057:Tomography, X-Ray Computed; D016896:Treatment Outcome