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Evaluation of an Early Regression Index (ERITCP) as Predictor of Pathological Complete Response in Cervical Cancer: A Pilot-Study
- Source :
- Applied Sciences, Volume 10, Issue 22, Applied Sciences, Vol 10, Iss 8001, p 8001 (2020)
- Publication Year :
- 2020
- Publisher :
- Multidisciplinary Digital Publishing Institute, 2020.
-
Abstract
- Background: Recent studies have highlighted the potentialities of a radiobiological parameter, the early regression index (ERITCP), in the treatment response prediction for rectal cancer patients treated with chemoradiotherapy followed by surgery. The aim of this study is to evaluate the performance of this parameter in predicting pathological complete response (pCR) in the context of low field MR guided radiotherapy (MRgRT) for cervical cancer (CC). Methods: A total of 16 patients affected by CC were enrolled. All patients underwent a MRgRT treatment, with prescription of 50.6 Gy in 22 fractions. A daily MR acquisition was performed at simulation and on each treatment fraction. Gross tumor volume (GTV) was delineated on the MR images acquired at the following biological effective dose (BED) levels: 14, 28, 42, 54 and 62 Gy. The ERITCP was calculated at the different BED levels and its predictive performance was quantified in terms of receiver operating characteristic (ROC) curve. Results: pCR was observed in 11/16 cases. The highest discriminative power of ERITCP was reported when a BED value of 28 Gy is reached, obtaining an area under curve (AUC) of 0.84. Conclusion: This study confirmed ERITCP as a promising response biomarker also for CC, although further studies with larger cohort of patients are recommended.
- Subjects :
- Colorectal cancer
cervical cancer
medicine.medical_treatment
Context (language use)
MR-guided radiotherapy
lcsh:Technology
030218 nuclear medicine & medical imaging
lcsh:Chemistry
03 medical and health sciences
0302 clinical medicine
Medicine
General Materials Science
lcsh:QH301-705.5
Instrumentation
Fluid Flow and Transfer Processes
Cervical cancer
Receiver operating characteristic
lcsh:T
business.industry
Process Chemistry and Technology
General Engineering
medicine.disease
predictive models
lcsh:QC1-999
Computer Science Applications
Radiation therapy
lcsh:Biology (General)
lcsh:QD1-999
lcsh:TA1-2040
030220 oncology & carcinogenesis
Cohort
Biomarker (medicine)
lcsh:Engineering (General). Civil engineering (General)
business
Nuclear medicine
lcsh:Physics
Chemoradiotherapy
Subjects
Details
- Language :
- English
- ISSN :
- 20763417
- Database :
- OpenAIRE
- Journal :
- Applied Sciences
- Accession number :
- edsair.doi.dedup.....ddfabe88d8d5bceaf2a5feaef91e25ab
- Full Text :
- https://doi.org/10.3390/app10228001