Dosimetrical and radiobiological approach to manage the dosimetric shift in the transition of dose calculation algorithm in radiation oncology: how to improve high quality treatment and avoid unexpected outcomes?

Impact of Dose Calculation Algorithms and Radiobiological Parameters on Prediction of Cardiopulmonary Complications in Left Breast Radiation Therapy

Background

Breast cancer requires evaluating treatment plans using dosimetric and biological parameters. Considering radiation dose distribution and tissue response, healthcare professionals can optimize treatment plans for better outcomes.

Objective

This study aimed to evaluate the effects of the different Dose Calculation Algorithms (DCAs) and Biologically Model-Related Parameters (BMRPs) on the prediction of cardiopulmonary complications due to left breast radiotherapy.

Material and Methods

In this practical study, the treatment plans of 21 female patients were simulated in the Monaco Treatment Planning System (TPS) with a prescribed dose of 50 Gy in 25 fractions. Dose distribution was extracted using the three DCAs [Pencil Beam (PB), Collapsed Cone (CC), and Monte Carlo (MC)]. Cardiopulmonary complications were predicted by Normal Tissue Complication Probability (NTCP) calculations using different dosimetric and biological parameters. The Lyman-Kutcher-Burman (LKB) and Relative-Seriality (RS) models were used to calculate NTCP. The endpoint for NTCP calculation was pneumonitis, pericarditis, and late cardiac mortality. The ANOVA test was used for statistical analysis.

Results

In calculating Tumor Control Probability (TCP), a statistically significant difference was observed between the results of DCAs in the Poisson model. The PB algorithm estimated NTCP as less than others for all Pneumonia BMRPs.

Conclusion

The impact of DCAs and BMRPs differs in the estimation of TCP and NTCP. DCAs have a stronger influence on TCP calculation, providing more effective results. On the other hand, BMRPs are more effective in estimating NTCP. Consequently, parameters for radiobiological indices should be cautiously used s to ensure the appropriate consideration of both DCAs and BMRPs.

Contouring variation affects estimates of normal tissue complication probability for breast fibrosis after radiotherapy

BACKGROUND

Normal tissue complication probability (NTCP) models can be useful to estimate the risk of fibrosis after breast-conserving surgery (BCS) and radiotherapy (RT) to the breast. However, they are subject to uncertainties. We present the impact of contouring variation on the prediction of fibrosis.

MATERIALS AND METHODS

280 breast cancer patients treated BCS-RT were included. Nine Clinical Target Volume (CTV) contours were created for each patient: i) CTV_crop (reference), cropped 5 mm from the skin and ii) CTV_skin, uncropped and including the skin, iii) segmenting the 95% isodose (Iso95%) and iv) 3 different auto-contouring atlases generating uncropped and cropped contours (Atlas_skin/Atlas_crop). To illustrate the impact of contour variation on NTCP estimates, we applied two equations predicting fibrosis grade ≥ 2 at 5 years, based on Lyman-Kutcher-Burman (LKB) and Relative Seriality (RS) models, respectively, to each contour. Differences were evaluated using repeated-measures ANOVA. For completeness, the association between observed fibrosis events and NTCP estimates was also evaluated using logistic regression.

RESULTS

There were minimal differences between contours when the same contouring approach was followed (cropped and uncropped). CTV_skin and Atlas_skin contours had lower NTCP estimates (-3.92%, IQR 4.00, p < 0.05) compared to CTV_crop. No significant difference was observed for Atlas_crop and Iso95% contours compared to CTV_crop. For the whole cohort, NTCP estimates varied between 5.3% and 49.5% (LKB) or 2.2% and 49.6% (RS) depending on the choice of contours. NTCP estimates for individual patients varied by up to a factor of 4. Estimates from "skin" contours showed higher agreement with observed events.

CONCLUSION

Contour variations can lead to significantly different NTCP estimates for breast fibrosis, highlighting the importance of standardising breast contours before developing and/or applying NTCP models.

Dosimetric Comparison of Different Dose Calculation Algorithms in Postmastectomy Breast Cancer Patients Using Conformal Planning Techniques

Background

The aim of the current study was to compare three different dose-calculating algorithms, i.e., superposition (SP), fast SP (FSP), and convolution (CV), for breast cancer patients treated with intensity-modulated radiotherapy (IMRT) and field-in-Field forward plan IMRT (FiF-FP-IMRT).

Materials and Methods

The current retrospective study involved 100 postmastectomy breast cancer patients who were given radiotherapy using IMRT and FiF-FP-IMRT planning techniques. All the initially SP-calculated plans were recalculated with the same monitor units for FSP and CV algorithm without change in any of the other planning parameters. The isodose distribution and various plan evaluating parameters, for example, conformity index (CI), homogeneity index, and uniformity index target volume and normal structure doses were compared and analyzed for all the different algorithm calculated plans.

Results

In the IMRT plans, all the target and normal structure dose-volume parameters showed a significant difference between all the three different algorithms with P < 0.05. In the FiF-FP-IMRT plans, CV algorithm showed a significant difference in most of the target and normal structure dose-volume parameters. Among quality indexes, only CI showed a significant difference between all the algorithms in both the planning techniques. R50 showed a significant difference with the CV algorithm in both the planning techniques.

Conclusion

The change in the dose calculation algorithm resulted in dosimetric changes which must be evaluated by the medical physicists and oncologists while evaluating treatment plans. In the current study with breast patients, the results obtained for target and normal structure doses using the CV algorithm are overestimated as compared to SP and FSP algorithms, producing variable results in air and bony normal structures. However, the ipsilateral lung V5 parameter and the ipsilateral humeral head mean dose were found to be underestimated by the CV algorithm as compared to the SP and FSP algorithm in both the planning techniques.

Dose to medium in head and neck radiotherapy: Clinical implications for target volume metrics

BACKGROUND AND PURPOSE

In radiotherapy dose calculation, advanced type-B dose calculation algorithms can calculate dose to medium (Dm ), as opposed to Type-B algorithms which compute dose to varying densities of water (Dw ). We investigate the impact of Dm on calculated dose and target coverage metrics in head and neck cancer patients.

METHODS AND MATERIALS

We reviewed 27 successfully treated (disease free at two-years post-(chemo)radiotherapy) human papillomavirus-associated (HPV) oropharyngeal cancer (ONC) patients treated with IMRT. Doses were calculated with Type-B and Linear Boltzman Transport Equation (LBTE) algorithms in a commercial treatment planning system, with the treated multi-leaf collimator patterns and monitor units. Coverage for primary Gross Tumour Volume (GTVp), high dose Planning Target Volume (PTV) (PTV_High), mandible within PTV_High (Mand ∩ PTV) and PTV_High excluding bone (PTV-bone) were compared between the algorithms.

RESULTS

Dose to 95% of PTV_High with LBTE was on average 1.1 Gy/1.7% lower than with Type-B (95%CI 1.5-1.9%, p < 0.0001). This magnitude was inversely linearly correlated with the relative volume of the PTV_High containing bone (pearson r = -0.81). Dose to 98% of the GTVp was 0.9 Gy/1.3% lower with LBTE compared with Type-B (95%CI 1.1-1.5%, p < 0.05). Dose to 98% of Mand ∩ PTV was on average 3.4 Gy/5.0% lower with LBTE than with Type-B (95%CI 4.6-5.4%, p < 0.0001).

CONCLUSION

In OPC treated with IMRT, Dm results in significant reductions in dose to bone in high dose PTVs. Reported GTVp dose was reduced, but by a lower magnitude. Reduced coverage metrics should be expected for OPC patients treated with IMRT, with dose reductions limited to regions of bone.