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

Abstract

Standard treatment for locally advanced cervical cancer (LACC) is chemoradiotherapy followed by brachytherapy. Despite radiation therapy advances, the toxicity rate remains significant. In this study, we compared the prediction of toxicity events after radiotherapy for locally advanced cervical cancer (LACC), based on either dose-volume histogram (DVH) parameters or the use of a radiomics approach applied to dose maps at the voxel level. Toxicity scores using the Common Terminology Criteria for Adverse Events (CTCAE v4), spatial dose distributions, and usual clinical predictors for the toxicity of 102 patients treated with chemoradiotherapy followed by brachytherapy for LACC were used in this study. In addition to usual DVH parameters, 91 radiomic features were extracted from rectum, bladder and vaginal 3D dose distributions, after discretization into a fixed bin width of 1 Gy. They were evaluated for predictive modelling of rectal, genitourinary (GU) and vaginal toxicities (grade ≥ 2). Logistic Normal Tissue Complication Probability (NTCP) models were derived using clinical parameters only or combinations of clinical, DVH and radiomics. For rectal acute/late toxicities, the area under the curve (AUC) using clinical parameters was 0.53/0.65, which increased to 0.66/0.63, and 0.76/0.87, with the addition of DVH or radiomics parameters, respectively. For GU acute/late toxicities, the AUC increased 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 increased from 0.51/0.57 (clinical only) to 0.58/0.72 (+DVH) and 0.82/0.89 (clinical + DVH + radiomics). The predictive performance of NTCP models based on radiomics features was higher than the commonly used clinical and DVH parameters. Dosimetric radiomics analysis is a promising tool for NTCP modelling in radiotherapy.

Multimodality radiomics prediction of radiotherapy-induced the early proctitis and cystitis in rectal cancer patients: a machine learning study

“…Developing predictive models for radiation-induced toxicity is crucial for optimizing radiotherapy dosages and enhancing patients' quality of life [14]. Artificial intelligence can predict potential complications in the rectum and bladder, such as proctitis and cystitis, by learning from previous cases [15].…”

Comparison of Jaw Mode and Field Width for Left-Breast Cancer Using TomoDirect Three-Dimensional Conformal Radiation Therapy: A Phantom Study

“…Being amenable to further refinements to maximize the heart sparing in left breast cancer irradiation, 3D-CRT is the most preferred and debated RT technique among the radiation oncologists treating these patient cohorts [ 9 , 10 ]. The dose-volume histogram (DVH) can verify quantitative assessment of the absorbed dose for the target and critical organs, and biological indexes such as the tumor control probability (TCP) and normal tissue complication probability (NTCP) also can predict the likelihood of radiation-induced complications in normal tissues and the local control rate of tumors [ 11 , 12 , 13 ].…”

Utilizing 3D Slicer to incorporate tomographic images into GATE Monte Carlo simulation for personalized dosimetry in yttrium‐90 radioembolization

“…It is convenient, providing fast computations and general image-guided therapy structure to support clinical conversion of experimental therapeutic methods and has been used in a lot of radiotherapy-related researches. [14][15][16] Segmentation and quantification using 3D Slicer can help analyze results from the MC simulation. A study on radiosynoviorthesis 17 had demonstrated the feasibility of segmentation and quantitation of radiological features on 3D MRI, where MC simulation was used to find the effective treatment range and S-value.…”

“…SlicerRT 13 is a free and open‐source extension available, which is intended for radiation therapy purposes. It is convenient, providing fast computations and general image‐guided therapy structure to support clinical conversion of experimental therapeutic methods and has been used in a lot of radiotherapy‐related researches 14–16 …”