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Delta-radiomics signature predicts treatment outcomes after preoperative chemoradiotherapy and surgery in rectal cancer
by
Song, Changhoon
, Kim, Bohyoung
, Chung, Jin Beom
, Kim, Jae-Sung
, Chang, Won
, Chie, Eui Kyu
, Chung, Joo-Hyun
, Lee, Yoon Jin
, Kim, Young Hoon
, Kang, Sung-Bum
, Jeon, Seung Hyuck
, Lee, Keun-Wook
in
Adenocarcinoma
/ Analysis
/ Biomarkers
/ Biomedical and Life Sciences
/ Biomedicine
/ Cancer
/ Cancer metastasis
/ Cancer Research
/ Cancer therapies
/ Chemoradiotherapy
/ Chemotherapy
/ Clinical outcomes
/ Clinical Radiation Oncology
/ Colorectal cancer
/ Delta-radiomics
/ Diagnosis
/ Feature extraction
/ Imaging
/ Magnetic resonance imaging
/ Medical imaging
/ Medical imaging equipment
/ Medical prognosis
/ Metastases
/ Metastasis
/ Multivariate analysis
/ NMR
/ Nuclear magnetic resonance
/ Oncology
/ Patients
/ Radiation therapy
/ Radiology
/ Radiomics
/ Radiotherapy
/ Rectal cancer
/ Rectum
/ Regression analysis
/ Researchers
/ Risk factors
/ Risk groups
/ Signatures
/ Surgery
/ Training
/ Treatment outcome
/ Urine
2019
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Delta-radiomics signature predicts treatment outcomes after preoperative chemoradiotherapy and surgery in rectal cancer
by
Song, Changhoon
, Kim, Bohyoung
, Chung, Jin Beom
, Kim, Jae-Sung
, Chang, Won
, Chie, Eui Kyu
, Chung, Joo-Hyun
, Lee, Yoon Jin
, Kim, Young Hoon
, Kang, Sung-Bum
, Jeon, Seung Hyuck
, Lee, Keun-Wook
in
Adenocarcinoma
/ Analysis
/ Biomarkers
/ Biomedical and Life Sciences
/ Biomedicine
/ Cancer
/ Cancer metastasis
/ Cancer Research
/ Cancer therapies
/ Chemoradiotherapy
/ Chemotherapy
/ Clinical outcomes
/ Clinical Radiation Oncology
/ Colorectal cancer
/ Delta-radiomics
/ Diagnosis
/ Feature extraction
/ Imaging
/ Magnetic resonance imaging
/ Medical imaging
/ Medical imaging equipment
/ Medical prognosis
/ Metastases
/ Metastasis
/ Multivariate analysis
/ NMR
/ Nuclear magnetic resonance
/ Oncology
/ Patients
/ Radiation therapy
/ Radiology
/ Radiomics
/ Radiotherapy
/ Rectal cancer
/ Rectum
/ Regression analysis
/ Researchers
/ Risk factors
/ Risk groups
/ Signatures
/ Surgery
/ Training
/ Treatment outcome
/ Urine
2019
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Delta-radiomics signature predicts treatment outcomes after preoperative chemoradiotherapy and surgery in rectal cancer
by
Song, Changhoon
, Kim, Bohyoung
, Chung, Jin Beom
, Kim, Jae-Sung
, Chang, Won
, Chie, Eui Kyu
, Chung, Joo-Hyun
, Lee, Yoon Jin
, Kim, Young Hoon
, Kang, Sung-Bum
, Jeon, Seung Hyuck
, Lee, Keun-Wook
in
Adenocarcinoma
/ Analysis
/ Biomarkers
/ Biomedical and Life Sciences
/ Biomedicine
/ Cancer
/ Cancer metastasis
/ Cancer Research
/ Cancer therapies
/ Chemoradiotherapy
/ Chemotherapy
/ Clinical outcomes
/ Clinical Radiation Oncology
/ Colorectal cancer
/ Delta-radiomics
/ Diagnosis
/ Feature extraction
/ Imaging
/ Magnetic resonance imaging
/ Medical imaging
/ Medical imaging equipment
/ Medical prognosis
/ Metastases
/ Metastasis
/ Multivariate analysis
/ NMR
/ Nuclear magnetic resonance
/ Oncology
/ Patients
/ Radiation therapy
/ Radiology
/ Radiomics
/ Radiotherapy
/ Rectal cancer
/ Rectum
/ Regression analysis
/ Researchers
/ Risk factors
/ Risk groups
/ Signatures
/ Surgery
/ Training
/ Treatment outcome
/ Urine
2019
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Delta-radiomics signature predicts treatment outcomes after preoperative chemoradiotherapy and surgery in rectal cancer
Journal Article
Delta-radiomics signature predicts treatment outcomes after preoperative chemoradiotherapy and surgery in rectal cancer
2019
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Overview
Background
To develop and compare delta-radiomics signatures from 2- (2D) and 3-dimensional (3D) features that predict treatment outcomes following preoperative chemoradiotherapy (CCRT) and surgery for locally advanced rectal cancer.
Methods
In total, 101 patients (training cohort,
n
= 67; validation cohort,
n
= 34) with locally advanced rectal adenocarcinoma between 2008 and 2015 were included. We extracted 55 features from T2-weighted magnetic resonance imaging (MRI) scans. Delta-radiomics feature was defined as the difference in radiomics feature before and after CCRT. Signatures were developed to predict local recurrence (LR), distant metastasis (DM), and disease-free survival (DFS) from 2D and 3D features. The least absolute shrinkage and selection operator regression was used to select features and build signatures. The delta-radiomics signatures and clinical factors were integrated into Cox regression analysis to determine if the signatures were independent prognostic factors.
Results
The radiomics signatures for LR, DM, and DFS were developed and validated using both 2D and 3D features. Outcomes were significantly different in the low- and high-risk patients dichotomized by optimal cutoff in both the training and validation cohorts. In multivariate analysis, the signatures were independent prognostic factors even when considering the clinical parameters. There were no significant differences in C-index from 2D vs. 3D signatures.
Conclusions
This is the first study to develop delta-radiomics signatures for rectal cancer. The signatures successfully predicted the outcomes and were independent prognostic factors. External validation is warranted to ensure their performance.
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