Toru Tochigi1,2, Sophia C Kamran3, Anushri Parakh1, Yoshifumi Noda1,4, Balaji Ganeshan5, Lawrence S Blaszkowsky6, David P Ryan6, Jill N Allen6, David L Berger7, Jennifer Y Wo3, Theodore S Hong3, Avinash Kambadakone8,9. 1. Department of Radiology, Massachusetts General Hospital, Boston, MA, USA. 2. Department of Frontier Surgery, Chiba University Graduate School of Medicine, Chiba, Japan. 3. Department of Radiation Oncology, Massachusetts General Hospital, Boston, MA, USA. 4. Department of Radiology, Gifu University, Gifu, Japan. 5. University College London, London, UK. 6. Department of Medical Oncology, Massachusetts General Hospital, Boston, MA, USA. 7. Department of Surgery, Massachusetts General Hospital, Boston, MA, USA. 8. Department of Radiology, Massachusetts General Hospital, Boston, MA, USA. akambadakone@mgh.harvard.edu. 9. Abdominal Imaging, Harvard Medical School, Massachusetts General Hospital, 55 Fruit Street, White 270, Boston, MA, 02114, USA. akambadakone@mgh.harvard.edu.
Abstract
OBJECTIVES: There are individual variations in neo-adjuvant chemoradiation therapy (nCRT) in patients with locally advanced rectal cancer (LARC). No reliable modality currently exists that can predict the efficacy of nCRT. The purpose of this study is to assess if CT-based fractal dimension and filtration-histogram texture analysis can predict therapeutic response to nCRT in patients with LARC. METHODS: In this retrospective study, 215 patients (average age: 57 years (18-87 years)) who received nCRT for LARC between June 2005 and December 2016 and underwent a staging diagnostic portal venous phase CT were identified. The patients were randomly divided into two datasets: a training set (n = 170), and a validation set (n = 45). Tumor heterogeneity was assessed on the CT images using fractal dimension (FD) and filtration-histogram texture analysis. In the training set, the patients with pCR and non-pCR were compared in univariate analysis. Logistic regression analysis was applied to identify the predictive value of efficacy of nCRT and receiver operating characteristic analysis determined optimal cutoff value. Subsequently, the most significant parameter was assessed in the validation set. RESULTS: Out of the 215 patients evaluated, pCR was reached in 20.9% (n = 45/215) patients. In the training set, 7 out of 37 texture parameters showed significant difference comparing between the pCR and non-pCR groups and logistic multivariable regression analysis incorporating clinical and 7 texture parameters showed that only FD was associated with pCR (p = 0.001). The area under the curve of FD was 0.76. In the validation set, we applied FD for predicting pCR and sensitivity, specificity, and accuracy were 60%, 89%, and 82%, respectively. CONCLUSION: FD on pretreatment CT is a promising parameter for predicting pCR to nCRT in patients with LARC and could be used to help make treatment decisions. KEY POINTS: • Fractal dimension analysis on pretreatment CT was associated with response to neo-adjuvant chemoradiation in patients with locally advanced rectal cancer. • Fractal dimension is a promising biomarker for predicting pCR to nCRT and may potentially select patients for individualized therapy.
OBJECTIVES: There are individual variations in neo-adjuvant chemoradiation therapy (nCRT) in patients with locally advanced rectal cancer (LARC). No reliable modality currently exists that can predict the efficacy of nCRT. The purpose of this study is to assess if CT-based fractal dimension and filtration-histogram texture analysis can predict therapeutic response to nCRT in patients with LARC. METHODS: In this retrospective study, 215 patients (average age: 57 years (18-87 years)) who received nCRT for LARC between June 2005 and December 2016 and underwent a staging diagnostic portal venous phase CT were identified. The patients were randomly divided into two datasets: a training set (n = 170), and a validation set (n = 45). Tumor heterogeneity was assessed on the CT images using fractal dimension (FD) and filtration-histogram texture analysis. In the training set, the patients with pCR and non-pCR were compared in univariate analysis. Logistic regression analysis was applied to identify the predictive value of efficacy of nCRT and receiver operating characteristic analysis determined optimal cutoff value. Subsequently, the most significant parameter was assessed in the validation set. RESULTS: Out of the 215 patients evaluated, pCR was reached in 20.9% (n = 45/215) patients. In the training set, 7 out of 37 texture parameters showed significant difference comparing between the pCR and non-pCR groups and logistic multivariable regression analysis incorporating clinical and 7 texture parameters showed that only FD was associated with pCR (p = 0.001). The area under the curve of FD was 0.76. In the validation set, we applied FD for predicting pCR and sensitivity, specificity, and accuracy were 60%, 89%, and 82%, respectively. CONCLUSION: FD on pretreatment CT is a promising parameter for predicting pCR to nCRT in patients with LARC and could be used to help make treatment decisions. KEY POINTS: • Fractal dimension analysis on pretreatment CT was associated with response to neo-adjuvant chemoradiation in patients with locally advanced rectal cancer. • Fractal dimension is a promising biomarker for predicting pCR to nCRT and may potentially select patients for individualized therapy.
Authors: H J Schmoll; E Van Cutsem; A Stein; V Valentini; B Glimelius; K Haustermans; B Nordlinger; C J van de Velde; J Balmana; J Regula; I D Nagtegaal; R G Beets-Tan; D Arnold; F Ciardiello; P Hoff; D Kerr; C H Köhne; R Labianca; T Price; W Scheithauer; A Sobrero; J Tabernero; D Aderka; S Barroso; G Bodoky; J Y Douillard; H El Ghazaly; J Gallardo; A Garin; R Glynne-Jones; K Jordan; A Meshcheryakov; D Papamichail; P Pfeiffer; I Souglakos; S Turhal; A Cervantes Journal: Ann Oncol Date: 2012-10 Impact factor: 32.976
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Authors: Fergus Davnall; Connie S P Yip; Gunnar Ljungqvist; Mariyah Selmi; Francesca Ng; Bal Sanghera; Balaji Ganeshan; Kenneth A Miles; Gary J Cook; Vicky Goh Journal: Insights Imaging Date: 2012-10-24