Tumor Volume Regression during and after Radiochemotherapy: A Macroscopic Description.
Paolo CastorinaGianluca FeriniEmanuele MartoranaStefano FortePublished in: Journal of personalized medicine (2022)
Tumor volume regression during and after chemo and radio therapy is a useful information for clinical decisions. Indeed, a quantitative, patient oriented, description of the response to treatment can guide towards the modification of the scheduled doses or the evaluation of the best time for surgery. We propose a macroscopic algorithm which permits to follow quantitatively the time evolution of the tumor volume during and after radiochemotherapy. The method, initially validated with different cell-lines implanted in mice, is then successfully applied to the available data for partially responding and complete recovery patients.
Keyphrases
- end stage renal disease
- locally advanced
- minimally invasive
- machine learning
- chronic kidney disease
- prognostic factors
- case report
- type diabetes
- combination therapy
- squamous cell carcinoma
- healthcare
- coronary artery bypass
- big data
- mass spectrometry
- acute coronary syndrome
- metabolic syndrome
- drug delivery
- peritoneal dialysis
- cancer therapy
- high fat diet induced
- health information
- artificial intelligence
- bone marrow