Identifying breast cancer patients who gain the most dosimetric benefit from deep inspiration breath hold radiotherapy

Dosimetric evaluation of the benefit of deep inspiration breath hold (DIBH) for locoregional irradiation of right breast cancer with volumetric modulated arctherapy (VMAT)

INTRODUCTION

Right-lateralized cardiac substructures can be substantially exposed during right breast cancer (R-BC) radiotherapy. The cardiac benefit of deep inspiration breath hold (DIBH) is established in combination with volumetric modulated arctherapy (VMAT) for left breast cancer with regional node irradiation but is unknown for R-BC. This study evaluated the dosimetric benefit of DIBH for locoregional irradiation of R-BC with VMAT.

MATERIAL AND METHODS

All patients treated for R-BC with adjuvant locoregional DIBH-VMAT in the Department of Radiation Oncology of the Institut Curie (Paris, France) until December 2022 were included, corresponding to 15 patients. FB- and DIBH-VMAT plans were compared both for a normofractionated regimen (50 Gy/25fx) used for treatment and a replanned hypofractionated regimen (40 Gy/15fx). Dose to the heart, cardiac substructures (sinoatrial node (SAN), atrio-ventricular node (AVN), right coronary artery, left anterior descending coronary artery, left ventricle), ipsilateral lung and liver were retrieved and compared.

RESULTS

Mean heart dose (MHD) was 3.33 Gy with FB vs. 3.10 Gy with DIBH on normofractionated plans (p = 0.489), and 2.58 Gy with FB vs. 2.41 Gy with DIBH on hypofractionated plan (p = 0.489). The benefit of DIBH was not significant for any cardiac substructure. The most exposed cardiac substructure were the SAN (mean dose of 6.62 Gy for FB- and 5.64 Gy for DIBH-VMAT on normofractionated plans) and the RCA (mean dose of 4.21 Gy for FB- and 4.06 Gy for DIBH-VMAT on normofractionated plans). The maximum benefit was observed for the RCA with a median individual dose reduction of 0.84 Gy on normofractionated plans (p = 0.599). No significant dosimetric difference were observed for right lung. Liver mean dose was significantly lower with DIBH with median values decreasing from 2.54 Gy to 0.87 Gy (p = 0.01).

CONCLUSION

Adding DIBH to efficient cardiac-sparing radiotherapy techniques, such as VMAT, is not justified in the general case for locoregional R-BC irradiation. Specific R-BC patient subpopulations who could benefit from additional DIBH combination with locoregional VMAT are yet to be identified.

Development of deep learning chest X-ray model for cardiac dose prediction in left-sided breast cancer radiotherapy

Deep inspiration breath-hold (DIBH) is widely used to reduce the cardiac dose in left-sided breast cancer radiotherapy. This study aimed to develop a deep learning chest X-ray model for cardiac dose prediction to select patients with a potentially high risk of cardiac irradiation and need for DIBH radiotherapy. We used 103 pairs of anteroposterior and lateral chest X-ray data of left-sided breast cancer patients (training cohort: n = 59, validation cohort: n = 19, test cohort: n = 25). All patients underwent breast-conserving surgery followed by DIBH radiotherapy: the treatment plan consisted of three-dimensional, two opposing tangential radiation fields. The prescription dose of the planning target volume was 42.56 Gy in 16 fractions. A convolutional neural network-based regression model was developed to predict the mean heart dose (∆MHD) reduction between free-breathing (MHD_FB) and DIBH. The model performance is evaluated as a binary classifier by setting the cutoff value of ∆MHD > 1 Gy. The patient characteristics were as follows: the median (IQR) age was 52 (47–61) years, MHD_FB was 1.75 (1.14–2.47) Gy, and ∆MHD was 1.00 (0.52–1.64) Gy. The classification performance of the developed model showed a sensitivity of 85.7%, specificity of 90.9%, a positive predictive value of 92.3%, a negative predictive value of 83.3%, and a diagnostic accuracy of 88.0%. The AUC value of the ROC curve was 0.864. The proposed model could predict ∆MHD in breast radiotherapy, suggesting the potential of a classifier in which patients are more desirable for DIBH.

Preoperative spirometry and BMI in deep inspiration breath-hold radiotherapy: the early detection of cardiac and lung dose predictors without radiation exposure

Background

This study aimed to investigate preoperative spirometry and BMI as early predictors of the mean heart and lung dose (MHD, MLD) in deep inspiration breath-hold (DIBH) radiotherapy.

Methods

Left-sided breast cancer patients underwent breast-conserving surgery followed by DIBH radiotherapy enrolled. Patients who were not available for preoperative spirometry were excluded. One hundred eligible patients were performed free-breathing (FB-) CT and DIBH-CT for plan comparison. We completed the correlative and multivariate analysis to develop the linear regression models for dose prediction. The residuals were calculated to explore the unpreferable subgroups and compare the prediction accuracy.

Results

Among the parameters, vital capacity (VC) and BMI showed the strongest negative correlation with MHD (r = − 0.33) and MLD (r = − 0.34), respectively. They were also significant in multivariate analysis (P < 0.001). Elderly and less VC were independent predictors of increasing absolute residuals (AR). The VC model showed no significant difference in AR compared to the model using the CT parameter of lung volume in FB (LV-FB): median AR of the LV-FB model vs. the VC model was 0.12 vs. 0.11 Gy (P = 0.79). On the other hand, the median AR of the MLD model was 0.38 Gy, showing no specific subgroups of larger AR.

Conclusion

Preoperative spirometry and BMI are significant predictors of MHD and MLD, respectively. Although elderly and low-VC patients may have larger predictive variations, spirometry might be a substitute for LV-FB as a predictor of MHD.