Dose-Response Model for Chest Wall Tolerance of Stereotactic Body Radiation Therapy

Kimsey, Frank C.; McKay, Jesse D.; Gefter, Jeffrey; Milano, Michael T.; Moiseenko, Vitali; Grimm, Jimm; Berg, Ronald

doi:10.1016/j.semradonc.2015.11.003

Cited by 19 publications

(17 citation statements)

References 31 publications

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“…Various dose-volume parameters such as D max , D 0.5cc , D 8.0cc and V 30 to V 70 have been shown to be significant risk factors for RIRFs [21, 22, 24, 26–28]. In a pooled analysis of patients undergoing SABR with 2 different types of treatment machine (LINAC and Cyberknife®), 10% risk level for grade 2 or higher chest wall complication for D 2cc was 43.0 Gy in 4 fractions [29]. A recent study by Okoukoni et al reported early cortical thinning of ribs after SABR in regions of receiving ≥10 Gy and suggested that rib thinning would contribute to the occurrence of rib fractures [30].…”

Section: Discussionmentioning

confidence: 99%

Predictors of chest wall toxicity after stereotactic ablative radiotherapy using real-time tumor tracking for lung tumors

2017

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BackgroundTo evaluate the incidence of chest wall toxicity after lung stereotactic ablative radiotherapy (SABR) and identify risk factors for the development of rib fracture.MethodsThirty-nine patients with 49 lesions underwent SABR for primary or metastatic lung tumors using Cyberknife® with tumor tracking systems. Patient characteristics, treatment factors and variables obtained from dose-volume histograms (DVHs) were analyzed to find the association with chest wall toxicity. Four-dimensional (4D) dose calculations were done to investigate the effect of respiratory motion on dose to the ribs.ResultsAfter follow-up of median 26.7 months (range: 8.4 – 80.0), 8 patients (20.5%) experienced rib fractures and among these patients, three (37.5%) had chest wall pain at 2–3 months after SABR. Median time to rib fracture was 13.4 months (range: 8.0 – 38.5) and the 2-year actuarial risk of rib fracture was 12.2%. Dose to the 4.6 cc of the ribs (D4.6cc) and rib volume received 160 Gy or more (V160) were significant predictor for rib fracture. No significant differences between three-dimensional (3D) and 4D dose calculations were found.ConclusionsParameters from DVH are useful in predicting the risk of chest wall toxicity after SABR for lung tumors. Efforts should be made to reduce the risk of the rib fracture after lung SABR.

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Section: Discussionmentioning

confidence: 99%

Predictors of chest wall toxicity after stereotactic ablative radiotherapy using real-time tumor tracking for lung tumors

2017

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“…A subset of prior studies of chest wall toxicity15, 16 have suggested that within the commonly used total dose and fractionation schemes for SBRT, dosimetric predictors do not result in significantly different rates of toxicity. However, this does not imply that rib and chest wall doses can be simply disregarded since (a) CWS can result without the clinical appearance of rib fractures and (b) increasing risk may still occur with increasing dose in a continuous fashion 18.…”

Section: Discussionmentioning

confidence: 99%

“…Global Dmax and fraction size are also suggested to be important indicators of toxicity, with higher rates of radiation‐induced rib fracture of ~50% for DMax > 54 Gy and fraction size >8 Gy 16. Regarding the chest wall specifically, constraints of V30 Gy < 70 cc,12 V30 Gy < 35 cc,13 and D30 cc < 30 Gy have been recommended 15. Kimsey et al.…”

Section: Discussionmentioning

confidence: 99%

“…All patients were planned with a constraint goal to keep 30 cc of the chest wall to <30.0 Gy. Twenty‐five parameters (termed features in the machine learning analysis) suspected of a correlation or previously reported10, 12, 13, 15, 17, 27, 28, 29, 30, 31 to associate with CWS were analyzed, including patient and tumor characteristics and dosimetric features were recorded for each patient. Toxicities were assessed using CTCAEv4 criteria for chest wall pain, where Grade 1 represents mild pain, Grade 2 represents moderate pain limiting instrumental activities of daily living (ADL), and Grade 3 represents severe pain limiting self‐care ADL.…”

Section: Methodsmentioning

confidence: 99%

“…A commonly used constraint is chest wall dose to 30 cc < 30 Gy,15 yet there is no prospectively validated data to support this threshold. There have been efforts in recent years to identify the risk factors for rib fractures and CWS and to refine the clinical and dosimetric predictors of chest wall toxicity using dose–response models 15, 16, 17, 18…”

Section: Introductionmentioning

confidence: 99%

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Exploratory analysis using machine learning to predict for chest wall pain in patients with stage I non‐small‐cell lung cancer treated with stereotactic body radiation therapy

Chao

Valdés

Luna

et al. 2018

J Applied Clin Med Phys

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Background and purposeChest wall toxicity is observed after stereotactic body radiation therapy (SBRT) for peripherally located lung tumors. We utilize machine learning algorithms to identify toxicity predictors to develop dose–volume constraints.Materials and methodsTwenty‐five patient, tumor, and dosimetric features were recorded for 197 consecutive patients with Stage I NSCLC treated with SBRT, 11 of whom (5.6%) developed CTCAEv4 grade ≥2 chest wall pain. Decision tree modeling was used to determine chest wall syndrome (CWS) thresholds for individual features. Significant features were determined using independent multivariate methods. These methods incorporate out‐of‐bag estimation using Random forests (RF) and bootstrapping (100 iterations) using decision trees.ResultsUnivariate analysis identified rib dose to 1 cc < 4000 cGy (P = 0.01), chest wall dose to 30 cc < 1900 cGy (P = 0.035), rib Dmax < 5100 cGy (P = 0.05) and lung dose to 1000 cc < 70 cGy (P = 0.039) to be statistically significant thresholds for avoiding CWS. Subsequent multivariate analysis confirmed the importance of rib dose to 1 cc, chest wall dose to 30 cc, and rib Dmax. Using learning‐curve experiments, the dataset proved to be self‐consistent and provides a realistic model for CWS analysis.ConclusionsUsing machine learning algorithms in this first of its kind study, we identify robust features and cutoffs predictive for the rare clinical event of CWS. Additional data in planned subsequent multicenter studies will help increase the accuracy of multivariate analysis.

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Clinical evidence for dose tolerance of the central nervous system in hypofractionated radiotherapy

et al. 2018

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Dose-Response Model for Chest Wall Tolerance of Stereotactic Body Radiation Therapy

Cited by 19 publications

References 31 publications

Predictors of chest wall toxicity after stereotactic ablative radiotherapy using real-time tumor tracking for lung tumors

Predictors of chest wall toxicity after stereotactic ablative radiotherapy using real-time tumor tracking for lung tumors

Exploratory analysis using machine learning to predict for chest wall pain in patients with stage I non‐small‐cell lung cancer treated with stereotactic body radiation therapy

Clinical evidence for dose tolerance of the central nervous system in hypofractionated radiotherapy

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