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. 2020 Nov;45(11):3608-3617.
doi: 10.1007/s00261-020-02502-w.

Clinical utility of radiomics at baseline rectal MRI to predict complete response of rectal cancer after chemoradiation therapy

Iva Petkovska #  1 , Florent Tixier #  2 , Eduardo J Ortiz  3 , Jennifer S Golia Pernicka  3 , Viktoriya Paroder  3 , David D Bates  3 , Natally Horvat  3 , James Fuqua  3 , Juliana Schilsky  3 , Marc J Gollub  3 , Julio Garcia-Aguilar  4 , Harini Veeraraghavan  2
Affiliations

Clinical utility of radiomics at baseline rectal MRI to predict complete response of rectal cancer after chemoradiation therapy

Iva Petkovska et al. Abdom Radiol (NY). 2020 Nov.

Abstract

Purpose: To investigate the value of T2-radiomics combined with anatomical MRI staging criteria from pre-treatment rectal MRI in predicting complete response to neoadjuvant chemoradiation therapy (CRT).

Methods: This retrospective study included patients with locally advanced rectal cancer who underwent rectal MRI before neoadjuvant CRT from October 2011 to January 2015 and then surgery. Surgical histopathologic analysis was used as the reference standard for pathologic complete response. Anatomical MRI staging criteria were extracted from our institutional standardized radiology report. In radiomics analysis, one radiologist manually segmented the primary tumor on T2-weighted images for all 102 patients (i.e., training set); two different radiologists independently segmented 66/102 patients (i.e., validation set). 108 radiomics features were extracted. Then, scanner-independent features were identified and least absolute shrinkage operator analysis was used to extract a radiomics score. Finally, a support vector machine model combining the radiomics score and anatomical MRI staging criteria was compared against both anatomical MRI-only and radiomics-only models using the deLong test.

Results: The study included 102 patients (42 women; median age = 61 years).The radiomics score produced an area under the curve (AUC) of 0.75. Comparable results were found using the validation set (AUCs = 0.75 and 0.71 for each radiologist, respectively). The anatomical MRI-only model had an accuracy of 67% (sensitivity 42%, specificity 72%); when adding the radiomics score, the accuracy increased to 74% (sensitivity 58%, specificity 77%).

Conclusion: Combining T2-radiomics and anatomical MRI staging criteria from pre-treatment rectal MRI may help to stratify patients based on the prediction of treatment response to neoadjuvant therapy.

Keywords: Computer-assisted; Image interpretation; Magnetic resonance imaging; Rectal cancer; Treatment outcome.

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Conflict of interest statement

Conflict of Interest: Dr. Garcia-Aguilar has received honoraria from Medtronic, Johnson & Johnson, and Intuitive Surgical. The remaining authors declare that they have no conflict of interest.

Figures

Fig. 1
Fig. 1
Flowchart of patient inclusion
Fig. 2
Fig. 2
Qualitative features assessed on rectal MRI in this study. (a) Tumor (arrow) length (yellow line); (b) T4a tumor (arrowhead) abutting anterior peritoneal reflection (arrow); (c) extramural vascular invasion (arrow), arrowhead pointing to tumor
Fig. 3
Fig. 3
Receiver operating curves showing the specificity and sensitivity of the radiomics score to identify pathologic complete response (pCR) patients (on the left) and boxplots showing the distribution of the radiomics score for pathologic partial response and pCR patients using the best cut-off value (on the right). a) Results based on manual segmentations of one radiologist for the entire cohort (n=102). b) and c) Results based on manual segmentations of two radiologists for a subset of patients (n=66) performed independently of each other
Fig. 4
Fig. 4
Importance of the selected features in the support vector machine models using a) anatomical MRI staging criteria and b) anatomical MRI staging criteria and the T2-radiomics score in combination
See this image and copyright information in PMC

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