Does restaging MRI radiomics analysis improve pathological complete response prediction in rectal cancer patients? A prognostic model development.
Adult
Aged
Aged, 80 and over
Cohort Studies
Female
Humans
Magnetic Resonance Imaging
/ methods
Male
Middle Aged
Neoadjuvant Therapy
/ methods
Neoplasm Staging
Predictive Value of Tests
Prognosis
Rectal Neoplasms
/ diagnostic imaging
Rectum
/ diagnostic imaging
Retrospective Studies
Treatment Outcome
Magnetic resonance imaging
Multidisciplinary tumor board
Neoadjuvant chemoradiation
Radiomics
Rectal cancer
Response prediction
Journal
La Radiologia medica
ISSN: 1826-6983
Titre abrégé: Radiol Med
Pays: Italy
ID NLM: 0177625
Informations de publication
Date de publication:
Jan 2022
Jan 2022
Historique:
received:
11
03
2021
accepted:
14
10
2021
pubmed:
3
11
2021
medline:
4
2
2022
entrez:
2
11
2021
Statut:
ppublish
Résumé
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). 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). 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. 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.
Identifiants
pubmed: 34725772
doi: 10.1007/s11547-021-01421-0
pii: 10.1007/s11547-021-01421-0
doi:
Types de publication
Journal Article
Langues
eng
Sous-ensembles de citation
IM
Pagination
11-20Informations de copyright
© 2021. Italian Society of Medical Radiology.
Références
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