microRNAs combined to radiomic features as a predictor of complete clinical response after neoadjuvant radio-chemotherapy for locally advanced rectal cancer: a preliminary study.
Pasquale LosurdoIlaria GandinManuel BelgranoIlaria FioreseRoberto VerardoFabrizio ZanconatiMaria Assunta CovaNicolò de ManziniPublished in: Surgical endoscopy (2023)
The pre-treatment identification of responders/NON-responders to nRCT could address patients to a personalized strategy, such as total neoadjuvant therapy (TNT) for responders and upfront surgery for non-responders. The combination of radiomic features and miRNAs expression data from images and biopsy obtained through standard of care has the potential to accelerate the discovery of a noninvasive multimodal approach to predict the cCR after nRCT for LARC.
Keyphrases
- rectal cancer
- locally advanced
- end stage renal disease
- lymph node
- healthcare
- newly diagnosed
- chronic kidney disease
- poor prognosis
- ejection fraction
- minimally invasive
- radiation therapy
- pain management
- palliative care
- prognostic factors
- squamous cell carcinoma
- small molecule
- deep learning
- peritoneal dialysis
- stem cells
- high throughput
- coronary artery bypass
- regulatory t cells
- bone marrow
- big data
- coronary artery disease
- convolutional neural network
- binding protein
- machine learning
- patient reported outcomes
- immune response
- long non coding rna
- patient reported
- affordable care act
- percutaneous coronary intervention
- replacement therapy