Radiation treatment planning

Dose-volume histogram

Cohort

Surgery

Rectum

Cervical cancer

Medical physics

Dosimetry

Radiation therapy

Radiology

Radiomics

Toxicity

Brachytherapy

Internal medicine

Oncology

Medicine

Nuclear medicine

Cancer

Logistic regression

International Journal of Radiation Oncology*Biology*Physics

Dose-volume histograms (DVH) do not account for the spatial distributions of dose at the voxel level. Our goal was to compare the prediction of toxicity events after radiotherapy for locally advanced cervical cancer (LACC), relying on either DVH parameters or the use of the radiomics approach applied to dose maps at the voxel level. Acute and late toxicity scores using the CTCAE v4, spatial dose distributions, and usual clinical predictors for toxicity, such as age and baseline symptoms, of 102 patients treated with chemoradiotherapy followed by brachytherapy for LACC were used in this study. Patients were split into training (patients treated in Brest, n = 52) and testing (patients treated in Quimper, n = 50) sets. In addition to usual DVH parameters, 91radiomic features (intensity and texture) of rectum, bladder and vaginal 3D dose distributions (defined using the organs at risk contours from the planning) were extracted after discretization into fixed bin width of 55 Gy, and evaluated for predictive modelling of rectal, genitourinary (GU) and vaginal toxicities. Logistic Normal Tissue Complication Probability (NTCP) models were derived, using only clinical parameters, clinical + DVH, clinical + radiomics, DVH + radiomics and clinical + DVH + radiomics combinations. In the entire cohort (training/testing), the cumulative rates of acute and late grade ≥2 rectal, GI and vaginal toxicities were 39%/42%, 14%/16%, 26%/28%, 10%/14%, 24%/24%, and 24%/24%, respectively. In the training cohort, for rectal acute/late toxicities, the area under the curve (AUC) using only clinical parameters was 0.53/0.65, which increased to 0.66/0.63, and 0.76/0.87, when adding DVH or radiomics parameters respectively. For GU acute/late toxicities, the AUC went up from 0.55/0.56 (clinical only), to 0.84/0.90 (+DVH) and 0.83/0.96 (clinical + DVH + radiomics). For vaginal acute/late toxicities, the AUC went up from 0.51/0.57 (clinical only), to 0.58/0.72 (+DVH) and 0.82/0.89 (clinical + DVH + radiomics). These trends were also confirmed by the AUCs of the final models evaluated in the testing cohort. For rectal acute/late toxicities, the AUC for using only clinical parameters was 0.55/0.56, which increased to 0.56/0.55, and 0.78/0.85, when adding DVH or radiomics parameters respectively. For GU acute/late toxicities, the AUC went up from 0.55/0.67 (clinical only), to 0.62/0.67 (+DVH) and 0.72/0.73 (clinical + DVH + radiomics). For vaginal acute/late toxicities, the AUC went up from 0.54/0.58 (clinical only), to 0.53/0.68 (+DVH) and 0.74/0.78 (clinical + DVH + radiomics). The predictive performance of NTCP models based on radiomics features is better than the commonly used DVH parameters. Dosimetric radiomics analysis is a promising tool for NTCP modelling in radiotherapy.

Radiomics Analysis of 3D Dose Distributions to Predict Toxicity of Radiotherapy for Cervical Cancer