Impact of dose escalation and adaptive radiotherapy for cervical cancers on tumour shrinkage—a modelling study

Fan beam CT-guided online adaptive external radiotherapy of uterine cervical cancer: a dosimetric evaluation

PURPOSE

To discuss the dosimetric advantages and reliability of the accurate delivery of online adaptive radiotherapy(online ART) for uterine cervical cancer(UCC).

METHODS AND MATERIALS

Six UCC patients were enrolled in this study. 95% of the planning target volume (PTV) reached 100% of the prescription dose (50.4 Gy/28fractions/6weeks) was required. The patients were scanned with uRT-Linac 506c KV-FBCT then the target volume (TV) and organs at risk (OARs) were delineated by doctors. The dosimeters designed and obtained a routine plan (Plan0). KV-FBCT was used for image guidance before subsequent fractional treatment. The online ART was processed after registration, which acquired a virtual nonadaptive radiotherapy plan (VPlan) and an adaptive plan (APlan). VPlan was the direct calculation of Plan0 on the fractional image, while APlan required adaptive optimization and calculation. In vivo dose monitoring and three-dimensional dose reconstruction were required during the implementation of APlan.

RESULTS

The inter-fractional volumes of the bladder and rectum changed greatly among the treatments. These changes influenced the primary gross tumor volume (GTVp) and the position deviation of GTVp and PTV and positively affected the prescription dose coverage of TV. GTVp decreased gradually along with dose accumulation. The Dmax, D98, D95, D50, and D2 of APlan were superior to those of VPlan in target dose distribution. APlan had good conformal index, homogeneity index and target coverage. The rectum V40 and Dmax, bladder V40, the small bowel V40 and Dmax of APlan were better than that of VPlan. The APlan's fractional mean γ passing rate was significantly higher than the international standard and the mean γ passing rate of all cases after the three-dimensional reconstruction was higher than 97.0%.

CONCLUSION

Online ART in external radiotherapy of UCC significantly improved the dose distribution and can become an ideal technology to achieve individualized precise radiotherapy.

Spatially fractionated radiotherapy: tumor response modelling including immunomodulation

A mathematical tumor response model has been developed, encompassing the interplay between immune cells and cancer cells initiated by either partial or full tumor irradiation. The iterative four-compartment model employs the linear-quadratic radiation response theory for four cell types: active and inactive cytotoxic T lymphocytes (immune cells, CD8⁺T cells in particular), viable cancer cells (undamaged and reparable cells) and doomed cells (irreparably damaged cells). The cell compartment interactions are calculated per day, with total tumor volume (TV) as the main quantity of interest. The model was fitted to previously published data on syngeneic xenografts (67NR breast carcinoma and Lewis lung carcinoma; (Markovskyet al2019Int. J. Radiat. Oncol. Biol. Phys.103697-708)) subjected to single doses of 10 or 15 Gy by 50% (partial) or 100% (full) TV irradiation. The experimental data included effects from anti-CD8⁺antibodies and immunosuppressive drugs. Using a new optimization method, promising fits were obtained where the lowest and highest root-mean-squared error values were observed for anti-CD8⁺treatment and unirradiated control data, respectively, for both cell types. Additionally, predictive capabilities of the model were tested by using the estimated model parameters to predict scenarios for higher doses and different TV irradiation fractions. Here, mean relative deviations in the range of 19%-34% from experimental data were found. However, more validation data is needed to conclude on the model's predictive capabilities. In conclusion, the model was found useful in evaluating the impact from partial and full TV irradiation on the immune response and subsequent tumor growth. The model shows potential to support and guide spatially fractionated radiotherapy in future pre-clinical and clinical studies.

Studying the regression profiles of cervical tumours during radiotherapy treatment using a patient-specific multiscale model

Apart from offering insight into the biomechanisms involved in cancer, many recent mathematical modeling efforts aspire to the ultimate goal of clinical translation, wherein models are designed to be used in the future as clinical decision support systems in the patient-individualized context. Most significant challenges are the integration of multiscale biodata and the patient-specific model parameterization. A central aim of this study was the design of a clinically-relevant parameterization methodology for a patient-specific computational model of cervical cancer response to radiotherapy treatment with concomitant cisplatin, built around a tumour features-based search of the parameter space. Additionally, a methodological framework for the predictive use of the model was designed, including a scoring method to quantitatively reflect the similarity and bilateral predictive ability of any two tumours in terms of their regression profile. The methodology was applied to the datasets of eight patients. Tumour scenarios in accordance with the available longitudinal data have been determined. Predictive investigations identified three patient cases, anyone of which can be used to predict the volumetric evolution throughout therapy of the tumours of the other two with very good results. Our observations show that the presented approach is promising in quantifiably differentiating tumours with distinct regression profiles.

An uncertainty metric to evaluate deformation vector fields for dose accumulation in radiotherapy

Background and purpose

In adaptive radiotherapy, deformable image registration (DIR) is used to propagate delineations of tumors and organs into a new therapy plan and to calculate the accumulated total dose. Many DIR accuracy metrics have been proposed. An alternative proposed here could be a local uncertainty (LU) metric for DIR results.

Materials and methods

The LU represented the uncertainty of each DIR position and was focused on deformation evaluation in uniformly-dense regions. Four cases demonstrated LU calculations: two head and neck cancer cases, a lung cancer case, and a prostate cancer case. Each underwent two CT examinations for radiotherapy planning.

Results

LU maps were calculated from each DIR of the clinical cases. Reduced fat regions had LUs of 4.6 ± 0.9 mm, 4.8 ± 1.0 mm, and 4.5 ± 0.7 mm, while the shrunken left parotid gland had a LU of 4.1 ± 0.8 mm and the shrunken lung tumor had a LU of 3.7 ± 0.7 mm. The bowels in the pelvic region had a LU of 10.2 ± 3.7 mm. LU histograms for the cases were similar and 99% of the voxels had a LU < 3 mm.

Conclusions

LU is a new uncertainty metric for DIR that was demonstrated for clinical cases. It had a tolerance of <3 mm.