Inter-institutional Variation in Intensity-modulated Radiotherapy for Breast Cancer in Korea (KROG 19-01).

BACKGROUND/AIM: To present the variations in the target delineation and the planning results of intensity-modulated radiation therapy (IMRT) for breast cancers. PATIENTS AND METHODS: We requested the target volumes and organs at risk delineation for two cases of left breast cancers, and evaluated the IMRT plans including the supraclavicular and internal mammary node irradiation. RESULTS: Twenty-one institutions participated in this study. Differences in the planning target volume among institutions reached up to three-times for breast-conserving surgery (BCS) case and five-times for mastectomy case. Mean heart doses ranged from 3.3 to 24.1 Gy for BCS case and from 5.0 to 26.5 Gy for mastectomy case. Ipsilateral lung volumes receiving more than 20 Gy ranged from 4.7 to 57.4% for BCS case and from 16.4 to 55.5% for mastectomy case. CONCLUSION: There were large variations in the target delineation and planning results of IMRT for breast cancers among institutions. Considering the increased use of breast IMRT, more standardized protocols are needed.

Advances in bowel delineation and dose-volume constraint in intensity modulated radiation therapy and 3D conformal radiation therapy for pelvic tumors / 中华放射医学与防护杂志

Intestinal injury is an important toxic response during radiation therapy of pelvic tumors. With the widespread use of precision radiotherapy techniques such as intensity modulated radiation therapy (IMRT), the dose exposed to normal tissues and organs has been significantly reduced. However, the toxic response of the bowel still limits the increase of the dose to the target volume. Therefore, the protection of important organs at risk (OAR), such as the bowel, becomes more and more important while giving adequate irradiated dose to the target volume. Most current studies used loop to contour bowel. For patients who underwent IMRT, the meaningful dose-volume predictors of grade 2 acute intestinal adverse events using bowel loop (small loop + big bowel) delineation included V45 Gy < 50 cm 3,V50 Gy < 13 cm 3, and V55 Gy < 3 cm 3, and the corresponding predicators using bowel bag delineation were V40 Gy < 170 cm 3,V45 Gy < 100 cm 3, and V50 Gy < 33 cm 3.

Dose-volume effects of breast cancer radiation therapy on the risk of second oesophageal cancer.

PURPOSE: To investigate the relationship between oesophagus dose-volume distribution and long-term risk of oesophageal cancer after radiation therapy for breast cancer. MATERIALS AND METHODS: In a case-control study nested within a cohort of 289,748 ≥5-year survivors of female breast cancer treated in 1943-2003 in five countries, doses to the second primary cancer (DSPC) and individual dose-volume histograms (DVH) to the entire oesophagus were reconstructed for 252 oesophageal cancer cases and 488 matched controls (median follow-up time: 13, range: 5-37 years). Using conditional logistic regression, we estimated excess odds ratios (EOR) of oesophageal cancer associated with DVH metrics. We also investigated whether DVH metrics confounded or modified DSPC-related -risk estimates. RESULTS: Among the DVH metrics evaluated, median dose (Dmedian) to the entire oesophagus had the best statistical performance for estimating risk of all histological types combined (EOR/Gy = 0.071, 95% confidence interval [CI]: 0.018 to 0.206). For squamous cell carcinoma, the most common subtype, the EOR/Gy for Dmedian increased by 31% (95% CI: 3% to 205%) for each increment of 10% of V30 (p = 0.02). Adjusting for DVH metrics did not materially change the EOR/Gy for DSPC, but there was a borderline significant positive interaction between DSPC and V30 (p = 0.07). CONCLUSION: This first study investigating the relationship between oesophagus dose-volume distribution and oesophageal cancer risk showed an increased risk per Gy for Dmedian with larger volumes irradiated at high doses. While current techniques allows better oesophagus sparing, constraints applied to Dmedian and V30 could potentially further reduce the risk of oesophageal cancer.

Integrating soft and hard dose-volume constraints into hierarchical constrained IMRT optimization.

PURPOSE: Dose-volume constraints (DVCs) continue to be common features in intensity-modulated radiation therapy (IMRT) prescriptions, but they are non-convex and difficult to incorporate. We propose computationally efficient methods to incorporate dose-volume constraints (DVCs) into automated IMRT planning. METHODS: We propose a two-phase approach: in phase-1, we solve a convex approximation with DVCs. Although this convex approximation does not guarantee DVC satisfaction, it provides crucial initial information about voxels likely to receive doses below DVC thresholds. Subsequently, phase-2 solves an optimization problem with maximum dose constraints imposed on those subthreshold voxels. We further categorize DVCs into hard- and soft-DVCs, where hard-DVCs are strictly enforced by the optimization and soft-DVCs are encouraged in the objective function. We tested this approach in our automated treatment planning system which is based on hierarchical constrained optimization. Performance is demonstrated on a series of paraspinal, lung, oligometastasis, and prostate cases as well as a small paraspinal case for which we can computationally afford to obtain a ground-truth by solving a non-convex optimization problem. RESULTS: The proposed algorithm successfully meets all the hard-DVCs while increasing the overall computational time of the baseline planning process (without DVCs) by 20%, 10%, and 11% for paraspinal, oligometastasis, and prostate cases, respectively. For a soft-DVC applied to the lung case, the dose-volume histogram curve moves toward the desired direction and the computational time is increased by 11%. For a low-resolution paraspinal case, the ground-truth solution process using mixed-integer programming methods required 15 h while the proposed algorithm converges in only 2 min with a proximal solution. CONCLUSIONS: A computationally tractable algorithm to handle hard- and soft-DVCs is developed which is capable of satisfying DVCs without any parameter tweaking. Although the algorithm is demonstrated in our in-house developed automated treatment planning system, it can potentially be used in any constrained optimization framework.

Dosimetric Predictors of Cardiotoxicity in Thoracic Radiotherapy for Lung Cancer.

BACKGROUND: Higher cardiac radiotherapy (RT) doses when treating lung cancer are associated with worse overall survival (OS), although the direct association between cardiac dose and early cardiotoxicity is poorly understood. We hypothesized that RT doses to the heart and cardiac substructures are associated with under-reported early cardiotoxicity and worse OS. PATIENTS AND METHODS: We conducted an institutional retrospective review of lung cancer patients treated with conventionally fractionated RT from 2010 to 2015. Collected data included pre-RT cardiac risk factors, post-RT cardiotoxicities, and dose-volume parameters for cardiac substructures. Univariate and multivariate analyses were performed to identify predictors of cardiotoxicity and OS. RESULTS: Seventy-six cases were evaluated with 1.2 years median follow-up. Cardiotoxicities included atrial arrhythmia (n = 5), pericardial effusion (n = 16), and valvular disease (n = 1). In univariate analysis, significant dose-volume predictors for cardiotoxicity included mean RT dose to structure of interest, volume of structure of interest receiving ≥30 Gy RT dose, and volume of structure of interest receiving ≥45 Gy RT dose (V45) to the atria, ventricles, and pericardium. Higher ventricular V45 was associated with post-RT cardiotoxicity in multivariate analysis (hazard ratio [HR], 1.50; P = .027). Cardiotoxicity occurrence was a highly significant predictor of OS in multivariate analysis (HR, 12.7; P < .001), but higher ventricular V45 alone was not (HR, 0.78; P = .450). CONCLUSION: Early cardiac events were relatively common after lung cancer RT and associated with multiple cardiac dose-volume parameters. Occurrence of early cardiotoxicity was strongly associated with worse OS. In practice, early cardiotoxicity is under-reported, supporting the need for more detailed cardiac evaluations in high-risk patients to detect and address early cardiotoxicity.

An Automatic Approach for Satisfying Dose-Volume Constraints in Linear Fluence Map Optimization for IMPT.

Prescriptions for radiation therapy are given in terms of dose-volume constraints (DVCs). Solving the fluence map optimization (FMO) problem while satisfying DVCs often requires a tedious trial-and-error for selecting appropriate dose control parameters on various organs. In this paper, we propose an iterative approach to satisfy DVCs using a multi-objective linear programming (LP) model for solving beamlet intensities. This algorithm, starting from arbitrary initial parameter values, gradually updates the values through an iterative solution process toward optimal solution. This method finds appropriate parameter values through the trade-off between OAR sparing and target coverage to improve the solution. We compared the plan quality and the satisfaction of the DVCs by the proposed algorithm with two nonlinear approaches: a nonlinear FMO model solved by using the L-BFGS algorithm and another approach solved by a commercial treatment planning system (Eclipse 8.9). We retrospectively selected from our institutional database five patients with lung cancer and one patient with prostate cancer for this study. Numerical results show that our approach successfully improved target coverage to meet the DVCs, while trying to keep corresponding OAR DVCs satisfied. The LBFGS algorithm for solving the nonlinear FMO model successfully satisfied the DVCs in three out of five test cases. However, there is no recourse in the nonlinear FMO model for correcting unsatisfied DVCs other than manually changing some parameter values through trial and error to derive a solution that more closely meets the DVC requirements. The LP-based heuristic algorithm outperformed the current treatment planning system in terms of DVC satisfaction. A major strength of the LP-based heuristic approach is that it is not sensitive to the starting condition.