Cancer risk assessment in modern radiotherapy workflow with medical big data.

Modern radiotherapy (RT) is being enriched by big digital data and intensive technology. Multimodality image registration, intelligence-guided planning, real-time tracking, image-guided RT (IGRT), and automatic follow-up surveys are the products of the digital era. Enormous digital data are created in the process of treatment, including benefits and risks. Generally, decision making in RT tries to balance these two aspects, which is based on the archival and retrieving of data from various platforms. However, modern risk-based analysis shows that many errors that occur in radiation oncology are due to failures in workflow. These errors can lead to imbalance between benefits and risks. In addition, the exact mechanism and dose-response relationship for radiation-induced malignancy are not well understood. The cancer risk in modern RT workflow continues to be a problem. Therefore, in this review, we develop risk assessments based on our current knowledge of IGRT and provide strategies for cancer risk reduction. Artificial intelligence (AI) such as machine learning is also discussed because big data are transforming RT via AI.

A parameterized model for mean urinary inflow rate and its preliminary application in radiotherapy for cervical cancer.

Forty-nine patients with stage IIb cervical cancer were included to investigate the changes in bladder volume in response to different approaches to maintaining consistent bladder filling. The impacts of age (P age), water consumption (P wat ), and body mass index (BMI, P bmi ) on the mean urinary inflow rate (v tot ) were analysed. The bladder volume (BV) increased linearly over time. A large variation in v tot among individuals was observed, ranging from 0.19 to 5.13 ml/min. The v tot was correlated with P age (R = -0.53, p = 0.01) and P wat (R = 0.84, p = 0.00), and no correlation between v tot and P bmi was found (p > 0.05). Therefore, v tot could be parameterized using two methods: multivariable linear regression and iterative fitting. There was no statistically significant difference between the two methods. The model accuracy was successfully assessed with several validation tests for patients with good compliance (79.2% of all patients), and the proportion of radiotherapy (RT) fractions with zero wait time (one ultrasound (US) scan) increased from 6.5% to 41.2%. The optimal US scanning number and RT time could be provided using this model. This adaptive RT approach could reduce patient discomfort caused by holding onto urine and reduce technician labour as well as cost.

Dosimetric evaluation of volumetric-modulated arc therapy (RapidArc) for primary leiomyosarcoma in the spine.

This study aims to investigate the suitability of volumetric-modulated arc therapy (VMAT) with RapidArc for primary leiomyosarcoma (LMS) in the spine, and present a new method to improve the target coverage and organs at risk (OAR) sparing. Five patients with LMS were retrospectively reviewed. The intensity-modulated radiotherapy (IMRT) with five coplanar beams (5b-IMRT) or seven coplanar beams (7b-IMRT), and VMAT using four quasi-quarter coplanar arcs (4q-VMAT) or two full coplanar arcs (2f-VMAT) were generated. Planning target volume (PTV) dose coverage, OAR dose sparing, conformity index (CI), and homogeneity index (HI) were evaluated. A hollow-cylinder model (HCM) was also used for feasible optimal beam arrangements. The mean doses to PTV were 95.2% ± 1.0%, 93.0% ± 1.0%, 97.9% ± 1.0% and 96.2% ± 1.5% for 4q-VMAT, 2f-VMAT, 5b-IMRT and 7b-IMRT respectively, while the mean maximum doses to spinal cord (SC) were 43.7 ± 0.9 Gy, 42.0 ± 0.8 Gy, 41.4 ± 1.2 Gy and 40.6 ± 1.4 Gy. Compared to 5b-IMRT, the mean doses delivered to kidneys decreased by about 35.1% (8.5 Gy), 2.5% (0.6 Gy) and 35.5% (8.6 Gy) for 4q-VMAT, 2f-VMAT, and 7b-IMRT, respectively. The CI proposed by Baltas et al. was twice as good with IMRT than with 4q-VMAT, and the numbers of monitor units were increased five- and threefold with 7b-IMRT and with 5b-IMRT compared to VMAT. The unexpected results we presented here show that VMAT technique can't achieve highly conformal treatment plans while maintaining SC sparing for LMS in the spine. An approach is proposed based on a hollow-cylinder model, but it is difficult to apply to clinical practice. In this case, VMAT is not superior to IMRT except for significant reduction in delivery time.