MRI radiomics features of mesorectal fat can predict response to neoadjuvant chemoradiation therapy and tumor recurrence in patients with locally advanced rectal cancer

Abstract

Objective: To interrogate the mesorectal fat using MRI radiomics feature analysis in order to predict clinical outcomes in patients with locally advanced rectal cancer.

Methods: This retrospective study included patients who underwent neoadjuvant chemoradiotherapy for locally advanced rectal cancer from 2009 to 2015. Three radiologists independently segmented mesorectal fat on baseline T2-weighted axial MRI. Radiomics features were extracted from segmented volumes and calculated using CERR software, with adaptive synthetic sampling being employed to combat large class imbalances. Outcome variables included pathologic complete response (pCR), local recurrence, distant recurrence, clinical T-category (cT), post-treatment T category (ypT), and post-treatment N category (ypN). A maximum of eight most important features were selected for model development using support vector machines and fivefold cross-validation to predict each outcome parameter via elastic net regularization. Diagnostic metrics of the final models were calculated, including sensitivity, specificity, PPV, NPV, accuracy, and AUC.

Results: The study included 236 patients (54 ± 12 years, 135 men). The AUC, sensitivity, specificity, PPV, NPV, and accuracy for each clinical outcome were as follows: for pCR, 0.89, 78.0%, 85.1%, 52.5%, 94.9%, 83.9%; for local recurrence, 0.79, 68.3%, 80.7%, 46.7%, 91.2%, 78.3%; for distant recurrence, 0.87, 80.0%, 88.4%, 58.3%, 95.6%, 87.0%; for cT, 0.80, 85.8%, 56.5%, 89.1%, 49.1%, 80.1%; for ypN, 0.74, 65.0%, 80.1%, 52.7%, 87.0%, 76.3%; and for ypT, 0.86, 81.3%, 84.2%, 96.4%, 46.4%, 81.8%.

Conclusion: Radiomics features of mesorectal fat can predict pathological complete response and local and distant recurrence, as well as post-treatment T and N categories.

Key points: • Mesorectal fat contains important prognostic information in patients with locally advanced rectal cancer (LARC). • Radiomics features of mesorectal fat were significantly different between those who achieved complete vs incomplete pathologic response (accuracy 83.9%, 95% CI: 78.6-88.4%). • Radiomics features of mesorectal fat were significantly different between those who did vs did not develop local or distant recurrence (accuracy 78.3%, 95% CI: 72.0-83.7% and 87.0%, 95% CI: 81.6-91.2% respectively).

Keywords: Adipose tissue; Magnetic resonance imaging; Neoadjuvant therapy; Rectal neoplasms.

Figure 1.

Flowchart of patient inclusion and exclusion. Abbreviations: LARC, locally advanced rectal cancer; MRI, magnetic resonance imaging; TNT, total neoadjuvant chemotherapy.

Figure 2.

Inter-reader agreement scores on two different patients. A, B and C; Segmentation of mesorectal fat by reader 1 (A), reader 2 (B), and reader 3 (C) in a 66-year-old female patient with rectal cancer, with a Jaccard index and dice similarity coefficient of 0.647 and 0.783, respectively. D, E and F; Segmentation of mesorectal fat by reader 1 (D), reader 2 (E), and reader 3 (F) in a 48-year-old female patient with rectal cancer, with a Jaccard index and dice similarity coefficient of 0.298 and 0.451, respectively.

Figure 3.

Area under the curve of the final radiomics model to predict pathologic complete response using eight radiomics features, calculated at 0.89 with a confidence interval of 0.83 to 0.96.

Figure 4.

Area under the curve of the final predictive radiomics model to predict local recurrence using eight radiomic features, calculated at 0.79 with a confidence interval of 0.71 to 0.88.

Figure 5:

Area under the curve of the final predictive model to predict distant recurrence using eight radiomics features, calculated at 0.87 with a confidence interval of 0.79 to 0.95.