Abstract
Purpose: Our study investigated the contribution that the application of radiomics analysis on post-treatment magnetic resonance imaging can add to the assessments performed by an experienced disease-specific multidisciplinary tumor board (MTB) for the prediction of pathological complete response (pCR) after neoadjuvant chemoradiotherapy (nCRT) in locally advanced rectal cancer (LARC). Materials and methods: This analysis included consecutively retrospective LARC patients who obtained a complete or near-complete response after nCRT and/or a pCR after surgery between January 2010 and September 2019. A three-step radiomics features selection was performed and three models were generated: a radiomics model (rRM), a multidisciplinary tumor board model (yMTB) and a combined model (CM). The predictive performance of models was quantified using the receiver operating characteristic (ROC) curve, evaluating the area under curve (AUC). Results: The analysis involved 144 LARC patients; a total of 232 radiomics features were extracted from the MR images acquired post-nCRT. The yMTB, rRM and CM predicted pCR with an AUC of 0.82, 0.73 and 0.84, respectively. ROC comparison was not significant (p = 0.6) between yMTB and CM. Conclusion: Radiomics analysis showed good performance in identifying complete responders, which increased when combined with standard clinical evaluation; this increase was not statistically significant but did improve the prediction of clinical response.
Lingua originale | English |
---|---|
pagine (da-a) | 11-20 |
Numero di pagine | 10 |
Rivista | LA RADIOLOGIA MEDICA |
Volume | 127 |
DOI | |
Stato di pubblicazione | Pubblicato - 2022 |
Keywords
- Adult
- Aged
- Aged, 80 and over
- Cohort Studies
- Female
- Humans
- Magnetic Resonance Imaging
- Magnetic resonance imaging
- Male
- Middle Aged
- Multidisciplinary tumor board
- Neoadjuvant Therapy
- Neoadjuvant chemoradiation
- Neoplasm Staging
- Predictive Value of Tests
- Prognosis
- Radiomics
- Rectal Neoplasms
- Rectal cancer
- Rectum
- Response prediction
- Retrospective Studies
- Treatment Outcome