title: NSCLC tumor shrinkage prediction using quantitative image features.
abstract: The objective of this study was to develop a quantitative image feature model to predict non-small cell lung cancer (NSCLC) volume shrinkage from pre-treatment CT images. 64 stage II-IIIB NSCLC patients with similar treatments were all imaged using the same CT scanner and protocol. For each patient, the planning gross tumor volume (GTV) was deformed onto the week 6 treatment image, and tumor shrinkage was quantified as the deformed GTV volume divided by the planning GTV volume. Geometric, intensity histogram, absolute gradient image, co-occurrence matrix, and run-length matrix image features were extracted from each planning GTV. Prediction models were generated using principal component regression with simulated annealing subset selection. Performance was quantified using the mean squared error (MSE) between the predicted and observed tumor shrinkages. Permutation tests were used to validate the results. The optimal prediction model gave a strong correlation between the observed and predicted tumor shrinkages with r=0.81 and MSE=8.60×10(-3). Compared to predictions based on the mean population shrinkage this resulted in a 2.92 fold reduction in MSE. In conclusion, this study indicated that quantitative image features extracted from existing pre-treatment CT images can successfully predict tumor shrinkage and provide additional information for clinical decisions regarding patient risk stratification, treatment, and prognosis.
authors.affiliation: Department of Radiation Physics, The University of Texas, MD Anderson Cancer Centre, 1515 Holcombe, Houston, TX 77030, USA.
authors.forename: Luke A
authors.initials: LA
authors.lastname: Hunter
authors.affiliation: Department of Radiation Physics, The University of Texas, MD Anderson Cancer Centre, 1515 Holcombe, Houston, TX 77030, USA.
authors.forename: Yi Pei
authors.initials: YP
authors.lastname: Chen
authors.affiliation: Department of Radiation Physics, The University of Texas, MD Anderson Cancer Centre, 1515 Holcombe, Houston, TX 77030, USA.
authors.forename: Lifei
authors.initials: L
authors.lastname: Zhang
authors.affiliation: Department of Radiation Physics, The University of Texas, MD Anderson Cancer Centre, 1515 Holcombe, Houston, TX 77030, USA.
authors.forename: Jason E
authors.initials: JE
authors.lastname: Matney
authors.affiliation: Department of Diagnostic Radiology, The University of Texas, MD Anderson Cancer Centre, 1515 Holcombe, Houston, TX 77030, USA.
authors.forename: Haesun
authors.initials: H
authors.lastname: Choi
authors.affiliation: Department of Radiation Physics, The University of Texas, MD Anderson Cancer Centre, 1515 Holcombe, Houston, TX 77030, USA.
authors.forename: Stephen F
authors.initials: SF
authors.lastname: Kry
authors.affiliation: Department of Radiation Physics, The University of Texas, MD Anderson Cancer Centre, 1515 Holcombe, Houston, TX 77030, USA.
authors.forename: Mary K
authors.initials: MK
authors.lastname: Martel
authors.affiliation: Department of Biostatistics, The University of Texas, MD Anderson Cancer Centre, 1515 Holcombe, Houston, TX 77030, USA.
authors.forename: Francesco
authors.initials: F
authors.lastname: Stingo
authors.affiliation: Department of Radiation Oncology, The University of Texas, MD Anderson Cancer Centre, 1515 Holcombe, Houston, TX 77030, USA.
authors.forename: Zhongxing
authors.initials: Z
authors.lastname: Liao
authors.affiliation: Department of Radiation Oncology, The University of Texas, MD Anderson Cancer Centre, 1515 Holcombe, Houston, TX 77030, USA.
authors.forename: Daniel
authors.initials: D
authors.lastname: Gomez
authors.affiliation: Department of Radiation Physics, The University of Texas, MD Anderson Cancer Centre, 1515 Holcombe, Houston, TX 77030, USA.
authors.forename: Jinzhong
authors.initials: J
authors.lastname: Yang
authors.affiliation: Department of Radiation Physics, The University of Texas, MD Anderson Cancer Centre, 1515 Holcombe, Houston, TX 77030, USA. Electronic address: lecourt@mdanderson.org.
authors.forename: Laurence E
authors.initials: LE
authors.lastname: Court
mesh_terms: D000465:Algorithms; D002289:Carcinoma, Non-Small-Cell Lung / Q000000981:diagnostic imaging* / Q000532:radiotherapy*; D006801:Humans; D008175:Lung Neoplasms / Q000000981:diagnostic imaging* / Q000532:radiotherapy*; D010363:Pattern Recognition, Automated / Q000379:methods; D011379:Prognosis; D011857:Radiographic Image Interpretation, Computer-Assisted / Q000379:methods; D061089:Radiotherapy, Image-Guided / Q000379:methods*; D015203:Reproducibility of Results; D012680:Sensitivity and Specificity; D013382:Subtraction Technique; D014057:Tomography, X-Ray Computed / Q000379:methods*; D016896:Treatment Outcome; D047368:Tumor Burden
keywords: NSCLC; Quantitative image feature; prediction; texture; tumor shrinkage