Microscopic disease extensions as a risk factor for loco-regional recurrence of NSCLC after SBRT

Radiomics-based discriminant analysis of principal components to stratify the treatment response of lung metastases following stereotactic body radiation therapy

PURPOSE

Discriminant analysis of principal components (DAPC) was introduced to describe the clusters of genetically related individuals focusing on the variation between the groups of individuals. Borrowing this approach, we evaluated the potential of DAPC for the evaluation of clusters in terms of treatment response to SBRT of lung lesions using radiomics analysis on pre-treatment CT images.

MATERIALS AND METHODS

80 pulmonary metastases from 56 patients treated with SBRT were analyzed. Treatment response was stratified as complete, incomplete and null responses. For each lesion, 107 radiomics features were extracted using the PyRadiomics software. The concordance correlation coefficients (CCC) between the radiomics features obtained by two segmentations were calculated. DAPC analysis was performed to infer the structure of "radiomically" related lesions for treatment response assessment. The DAPC was performed using the "adegenet" package for the R software.

RESULTS

The overall mean CCC was 0.97 ± 0.14. The analysis yields 14 dimensions in order to explain 95 % of the variance. DAPC was able to group the 80 lesions into the 3 different clusters based on treatment response depending on the radiomics features characteristics. The first Linear Discriminant achieved the best discrimination of individuals into the three pre-defined groups. The greater radiomics loadings who contributed the most to the treatment response differentiation were associated with the "sphericity", "correlation" and "maximal correlation coefficient" features.

CONCLUSION

This study demonstrates that a DAPC analysis based on radiomics features obtained from pretreatment CT is able to provide a reliable stratification of complete, incomplete or null response of lung metastases following SBRT.

Predicting cancer relapse following lung stereotactic radiotherapy: an external validation study using real-world evidence

Purpose

For patients receiving lung stereotactic ablative radiotherapy (SABR), evidence suggests that high peritumor density predicts an increased risk of microscopic disease (MDE) and local-regional failure, but only if there is low or heterogenous incidental dose surrounding the tumor (GTV). A data-mining method (Cox-per-radius) has been developed to investigate this dose-density interaction. We apply the method to predict local relapse (LR) and regional failure (RF) in patients with non-small cell lung cancer.

Methods

199 patients treated in a routine setting were collated from a single institution for training, and 76 patients from an external institution for validation. Three density metrics (mean, 90th percentile, standard deviation (SD)) were studied in 1mm annuli between 0.5cm inside and 2cm outside the GTV boundary. Dose SD and fraction of volume receiving less than 30Gy were studied in annuli 0.5-2cm outside the GTV to describe incidental MDE dosage. Heat-maps were created that correlate with changes in LR and RF rates due to the interaction between dose heterogeneity and density at each distance combination. Regions of significant improvement were studied in Cox proportional hazards models, and explored with and without re-fitting in external data. Correlations between the dose component of the interaction and common dose metrics were reported.

Results

Local relapse occurred at a rate of 6.5% in the training cohort, and 18% in the validation cohort, which included larger and more centrally located tumors. High peritumor density in combination with high dose variability (0.5 - 1.6cm) predicts LR. No interactions predicted RF. The LR interaction improved the predictive ability compared to using clinical variables alone (optimism-adjusted C-index; 0.82 vs 0.76). Re-fitting model coefficients in external data confirmed the importance of this interaction (C-index; 0.86 vs 0.76). Dose variability in the 0.5-1.6 cm annular region strongly correlates with heterogeneity inside the target volume (SD; ρ = 0.53 training, ρ = 0.65 validation).

Conclusion

In these real-world cohorts, the combination of relatively high peritumor density and high dose variability predicts increase in LR, but not RF, following lung SABR. This external validation justifies potential use of the model to increase low-dose CTV margins for high-risk patients.

CT-based radiomics prediction of complete response after stereotactic body radiation therapy for patients with lung metastases

PURPOSE

Stereotactic body radiotherapy (SBRT) is a key treatment modality for lung cancer patients. This study aims to develop a machine learning-based prediction model of complete response for lung oligometastatic cancer patients undergoing SBRT.

MATERIALS AND METHODS

CT images of 80 pulmonary oligometastases from 56 patients treated with SBRT were analyzed. The gross tumor volumes (GTV) were contoured on CT images. Patients that achieved complete response (CR) at 4 months were defined as responders. For each GTV, 107 radiomic features were extracted using the Pyradiomics software. The concordance correlation coefficients (CCC) between the region of interest (ROI)-based radiomics features obtained by the two segmentations were calculated. Pairwise feature interdependencies were evaluated using the Spearman rank correlation coefficient. The association of clinical variables and radiomics features with CR was evaluated with univariate logistic regression. Two supervised machine learning models, the logistic regression (LR) and the classification and regression tree analysis (CART), were trained to predict CR. The models were cross-validated using a five-fold cross-validation. The performance of models was assessed by receiver operating characteristic curve (ROC) and class-specific accuracy, precision, recall, and F1-measure evaluation metrics.

RESULTS

Complete response was associated with four radiomics features, namely the surface to volume ratio (SVR; p = 0.003), the skewness (Skew; p = 0.027), the correlation (Corr; p = 0.024), and the grey normalized level uniformity (GNLU; p = 0.015). No significant relationship between clinical parameters and CR was found. In the validation set, the developed LR and CART machine learning models had an accuracy, precision, and recall of 0.644 and 0.750, 0.644 and 0.651, and 0.635 and 0.754, respectively. The area under the curve for CR prediction was 0.707 and 0.753 for the LR and CART models, respectively.

CONCLUSION

This analysis demonstrates that radiomics features obtained from pretreatment CT could predict complete response of lung oligometastases following SBRT.

Radial Data Mining to Identify Density-Dose Interactions That Predict Distant Failure Following SABR

Purpose

Lower dose outside the planned treatment area in lung stereotactic radiotherapy has been linked to increased risk of distant metastasis (DM) possibly due to underdosage of microscopic disease (MDE). Independently, tumour density on pretreatment computed tomography (CT) has been linked to risk of MDE. No studies have investigated the interaction between imaging biomarkers and incidental dose. The interaction would showcase whether the impact of dose on outcome is dependent on imaging and, hence, if imaging could inform which patients require dose escalation outside the gross tumour volume (GTV). We propose an image-based data mining methodology to investigate density-dose interactions radially from the GTV to predict DM with no a priori assumption on location.

Methods

Dose and density were quantified in 1-mm annuli around the GTV for 199 patients with early-stage lung cancer treated with 60 Gy in 5 fractions. Each annulus was summarised by three density and three dose parameters. For parameter combinations, Cox regressions were performed including a dose-density interaction in independent annuli. Heatmaps were created that described improvement in DM prediction due to the interaction. Regions of significant improvement were identified and studied in overall outcome models.

Results

Dose-density interactions were identified that significantly improved prediction for over 50% of bootstrap resamples. Dose and density parameters were not significant when the interaction was omitted. Tumour density variance and high peritumour density were associated with DM for patients with more cold spots (less than 30-Gy EQD2) and non-uniform dose about 3 cm outside of the GTV. Associations identified were independent of the mean GTV dose.

Conclusions

Patients with high tumour variance and peritumour density have increased risk of DM if there is a low and non-uniform dose outside the GTV. The dose regions are independent of tumour dose, suggesting that incidental dose may play an important role in controlling occult disease. Understanding such interactions is key to identifying patients who will benefit from dose-escalation. The methodology presented allowed spatial dose-density interactions to be studied at the exploratory stage for the first time. This could accelerate the clinical implementation of imaging biomarkers by demonstrating the impact of incidental dose for tumours of varying characteristics in routine data.

Impact of dose to lung outside the planning target volume on distant metastasis or progression after SBRT for early-stage non-small cell lung cancer

Mean dose (EQD2) to 3-cm shell of lung surrounding the PTV was evaluated for association with distant metastasis and PFS after SBRT for stage I NSCLC. Dose was uniformly above previously determined threshold and metastasis was uncommon. An association between outcomes and mean EQD2 could not be confirmed or refuted.

Can dosimetry affect local control and survival in patients with early-stage lung cancer treated with Stereotactic Ablative Radiotherapy (SABR)? An analysis of the UK's largest cohort of lung SABR patients

PURPOSE/OBJECTIVES

A recent study has shown that tight conformity of lung Stereotactic Ablative Radiotherapy (SABR) plans might worsen loco-regional control and can predict distant metastases. The study aims to report overall survival (OS), progression-free survival (PFS), local recurrence free survival (LRFS), and dosimetry of early-stage lung cancer patients treated with SABR and to try to explore any dosimetric predictor of outcomes.

MATERIAL AND METHODS

Patients treated in our institute (May 2009-August 2018) were included. Electronic medical records were reviewed for baseline characteristics, treatment details, and outcomes. Dosimetric data were extracted from Xio and Monaco software. Patients were treated according to the United Kingdom (UK) SABR consortium guidelines. Kaplan-Meier's analysis with log-rank test was used for survival analysis. The univariate and multivariable Cox regression model was used for correlating dosimetric variables and outcomes.

RESULTS

We treated 1266 patients with median age of 75 years and 47.4% were male. Median follow up was 56 months. Median OS was 36 months with 1, 2, and 5 years OS of 84.2%, 64.5%, and 31.5%, respectively. Median for PFS and LRFS was not reached. One, 2, and 5 years PFS were 87.4%, 78.4%, and 72.5%, respectively. One, 2, and 5 years LRFS were 98.2%, 95.1%, and 92.5%, respectively. Planning target volume (PTV), dose to 99% volume of PTV (D99), and R50 (volume receiving the 50% dose/volume (PTV)) were significantly associated with OS. PTV, mean lung dose (MLD), V20 (volume of lung minus gross tumour volume (GTV) receiving 20 Gy), V12.5 (volume of lung minus GTV receiving 12.5 Gy), and dose fractionation were significantly associated with PFS. Nothing was associated with LRFS on univariate analysis. R100 of >1.1 was associated with better OS, PFS, and LRFS compared to R100 ≤ 1.1.

CONCLUSION

SABR achieves good clinical outcomes in patients with early-stage lung cancer; even in elderly patients with multiple comorbidities. In the largest UK early lung cancer cohort treated with SABR, we found that dosimetry correlates with clinical outcomes. Further validation of these results is needed to guide future optimisation of SABR delivery.

Automated gross tumor volume contour generation for large-scale analysis of early-stage lung cancer patients planned with 4D-CT

PURPOSE

Patients with early-stage lung cancer undergoing stereotactic ablative radiotherapy receive four-dimensional computed tomography (4D-CT) for treatment planning. Often, an internal gross target volume (iGTV), which approximates the motion envelope of a tumor over the breathing cycle, is delineated without defining a gross tumor volume (GTV). However, the GTV volume and shape are important parameters for prognostic and dose modelling, and there is interest in radiomic features extracted from the GTV and surrounding tissue. We demonstrate and validate a method to generate the GTV from an iGTV contour to aid retrospective analysis on routine data.

METHOD

It is possible to reconstruct the geometry of a tumor with knowledge of tumor motion and the motion envelope formed during respiration. To demonstrate this, the tumor motion path was estimated with local rigid registration, and the iGTV positioned incrementally at stations along the reverse path. It is shown that the tumor volume is the largest set common to the intersection of the iGTV at these positions, hence can be derived. This was implemented for 521 lung lesions on 4D-CT. Eleven patients with a GTV delineation performed by a radiation oncologist on a reference phase (50%) were used for validation. The generated GTV was compared to that delineated by the expert using distance-to-agreement (DTA), volume, and distance between centres of mass. An overall success rate was determined by detecting registration inaccuracy and performing a quality check on the routine iGTV. For successfully generated contours, GTV volume was compared to iGTV volume in a prognostic model for overall survival.

RESULTS

For the validation dataset, DTA mean (0.79 - 1.55 mm) and standard deviation (0.68 - 1.51 mm) were comparable to expected observer variation. Difference in volume was < 5 cm³ , and average difference in position was 1.21 mm. Deviations in shape and position were mainly caused by observer differences in iGTV and GTV interpretation as opposed to algorithm performance. For the complete dataset, an acceptable contour was generated for 94% of patients using statistical and visual assessment to detect failures. Generated GTV volumes improved prognostic model performance over iGTV volumes.

CONCLUSION

A method to generate a GTV from an iGTV and 4D-CT dataset was developed. This method facilitates data analysis of patients with early-stage lung cancer treated in the routine setting, that is, data mining, prognostic modeling, and radiomics. Generation failure detection removes the need for visual assessment of all contours, reducing a time-consuming aspect of big-data analysis. Favorable prognostic performance of generated GTV volumes over iGTV ones demonstrates opportunities to use this methodology for future study.

Oncologic Outcomes of Surgery Versus SBRT for Non-Small-Cell Lung Carcinoma: A Systematic Review and Meta-analysis

BACKGROUND

The optimal treatment of stage I non-small-cell lung carcinoma is subject to debate. The aim of this study was to compare overall survival and oncologic outcomes of lobar resection (LR), sublobar resection (SR), and stereotactic body radiotherapy (SBRT).

METHODS

A systematic review and meta-analysis of oncologic outcomes of propensity matched comparative and noncomparative cohort studies was performed. Outcomes of interest were overall survival and disease-free survival. The inverse variance method and the random-effects method for meta-analysis were utilized to assess the pooled estimates.

RESULTS

A total of 100 studies with patients treated for clinical stage I non-small-cell lung carcinoma were included. Long-term overall and disease-free survival after LR was superior over SBRT in all comparisons, and for most comparisons, SR was superior to SBRT. Noncomparative studies showed superior long-term overall and disease-free survival for both LR and SR over SBRT. Although the papers were heterogeneous and of low quality, results remained essentially the same throughout a large number of stratifications and sensitivity analyses.

CONCLUSION

Results of this systematic review and meta-analysis showed that LR has superior outcomes compared to SBRT for cI non-small-cell lung carcinoma. New trials are underway evaluating long-term results of SBRT in potentially operable patients.

[Prognosis factors after lung stereotactic body radiotherapy for non-small cell lung carcinoma]

Lung cancer is the fourth most common cancer in France with a prevalence of 30,000 new cases per year. Lobectomy surgery with dissection is the gold standard treatment for T1-T2 localized non-small cell lung carcinoma. A segmentectomy may be proposed to operable patients but fragile from a respiratory point of view. For inoperable patients or patients with unsatisfactory pulmonary function tests, local treatment with stereotactic radiotherapy may be proposed to achieve local control rates ranging from 85 to 95% at 3-5 years. Several studies have examined prognostic factors after stereotaxic pulmonary radiotherapy. We conducted a general review of the literature to identify factors affecting local control.

Comparing local control and distant metastasis in NSCLC patients between CyberKnife and conventional SBRT

BACKGROUND AND PURPOSE

Previous literature suggests that the dose proximally outside the PTV could have an impact on the incidence of distant metastasis (DM) after SBRT in stage I NSCLC patients. We investigated this observation (along with local failure) in deliveries made by different treatment modalities: robotic mounted linac SBRT (CyberKnife) vs conventional SBRT (VMAT/CRT).

MATERIALS AND METHODS

This study included 422 stage I NSCLC patients from 2 institutions who received SBRT: 217 treated conventionally and 205 with CyberKnife. The dose behavior outside the PTV of both sub-cohorts were compared by analyzing the mean dose in continuous shells extending 1, 2, 3, …, 100 mm from the PTV. Kaplan-Meier analysis was performed between the two sub-cohorts with respect to DM-free survival and local progression-free survival. A multivariable Cox proportional hazards model was fitted to the combined cohort (n = 422) with respect to DM incidence and local failure.

RESULTS

The shell-averaged dose fall-off beyond the PTV was found to be significantly more modest in CyberKnife plans than in conventional SBRT plans. In a 30 mm shell around the PTV, the mean dose delivered with CyberKnife (38.1 Gy) is significantly larger than with VMAT/CRT (22.8 Gy, p<10^-8). For 95% of CyberKnife plans, this region receives a mean dose larger than the 21 Gy threshold dose discovered in our previous study. In contrast, this occurs for only 75% of VMAT/CRT plans. The DM-free survival of the entire CyberKnife cohort is superior to that of the 25% of VMAT/CRT patients receiving less than the threshold dose (VMAT/CRT_<21Gy), with a hazard ratio of 5.3 (95% CI: 3.0-9.3, p<10^-8). The 2 year DM-free survival rates were 87% (95% CI: 81%-91%) and 44% (95% CI: 28%-58%) for CyberKnife and the below-threshold dose conventional cohorts, respectively. A multivariable analysis of the combined cohort resulted in the confirmation that threshold dose was a significant predictor of DM(HR = 0.28, 95% CI: 0.15-0.55, p<10^-3) when adjusted for other clinical factors. CyberKnife was also found to be superior to the entire VMAT/CRT with respect to local control (HR = 3.44, CI: 1.6-7.3). The 2-year local progression-free survival rates for the CyberKnife cohort and the VMAT/CRT cohort were 96% (95% CI: 92%-98%) and 88% (95% CI: 82%-92%) respectively.

CONCLUSIONS

In standard-of-care CyberKnife treatments, dose distributions that aid distant control are achieved 95% of the time. Although similar doses could be physically achieved by conventional SBRT, this is not always the case with current prescription practices, resulting in worse DM outcomes for 25% of conventional SBRT patients. Furthermore, CyberKnife was found to provide superior local control compared to VMAT/CRT.

Is tumour sphericity an important prognostic factor in patients with lung cancer?

BACKGROUND AND PURPOSE

Quantitative tumour shape features extracted from radiotherapy planning scans have shown potential as prognostic markers. In this study, we investigated if sphericity of the gross tumour volume (GTV) on planning computed tomography (CT) is an independent predictor of overall survival (OS) in lung cancer patients treated with standard radiotherapy. In the analysis, we considered whether tumour sphericity is correlated with clinical prognostic factors or influenced by the inclusion of lymph nodes in the GTV.

MATERIALS AND METHODS

Sphericity of single GTV delineation was extracted for 457 lung cancer patients. Relationships between sphericity, and common patient and tumour characteristics were investigated via correlation analysis and multivariate Cox regression to assess prognostic value of GTV sphericity. A subset analysis was performed for 290 nodal stage N0 patients to determine prognostic value of primary tumour sphericity.

RESULTS

Sphericity is correlated with clinical variables: tumour volume, mean lung dose, N stage, and T stage. Sphericity is strongly associated with OS (p < 0.001, hazard ratio (HR) (95% confidence interval (CI)) = 0.13 (0.04-0.41)) in univariate analysis. However, this association did not remain significant in multivariate analysis (p = 0.826, HR (95% CI) = 0.83 (0.16-4.31), and inclusion of sphericity to a clinical model did not improve model performance. In addition, no significant relationship between sphericity and OS was detected in univariate (p = 0.072) or multivariate (p = 0.920) analysis of N0 subset.

CONCLUSION

Sphericity correlates clearly with clinical prognostic factors, which are often unaccounted for in radiomic studies. Sphericity is also influenced by the presence of nodal involvement within the GTV contour.

Can dose outside the PTV influence the risk of distant metastases in stage I lung cancer patients treated with stereotactic body radiotherapy (SBRT)?

BACKGROUND AND PURPOSE

In an era where little is known about the "abscopal" (out-of-the-field) effects of lung SBRT, we investigated correlations between the radiation dose proximally outside the PTV and the risk of cancer recurrence after SBRT in patients with primary stage I non-small cell lung cancer (NSCLC).

MATERIALS AND METHODS

This study included 217 stage I NSCLC patients across 2 institutions who received SBRT. Correlations between clinical and dosimetric factors were investigated. The clinical factors considered were distant metastasis (DM), loco-regional control (LRC) and radiation pneumonitis (RP). The dose (converted to EQD2) delivered to regions of varying size directly outside of the PTV was computed. For each feature, area under the curve (AUC) and odds ratios with respect to the outcome parameters DM, LRC and RP were estimated; Kaplan-Meier (KM) analysis was also performed.

RESULTS

Thirty-seven (17%) patients developed DM after a median follow-up of 24 months. It was found that the mean dose delivered to a shell-shaped region of thickness 30 mm outside the PTV had an AUC of 0.82. Two years after treatment completion, the rate of DM in patients where the mean dose delivered to this region was higher than 20.8 Gy₂ was 5% compared to 60% in those who received a dose lower than 20.8 Gy₂. KM analysis resulted in a hazard ratio of 24.2 (95% CI: 10.7, 54.4); p < 10^-5. No correlations were found between any factor and either LRC or RP.

CONCLUSIONS

The results of this study suggest that the dose received by the region close to the PTV has a significant impact on the risk of distant metastases in stage I NSCLC patients treated with SBRT. If these results are independently confirmed, caution should be taken, particularly when a treatment plan results in a steep dose gradient extending outwards from the PTV.

[Stereotactic lung radiotherapy: Technical setting up on Novalis Tx® and single centre prospective study of the 100 first malignant pulmonary nodules treated at centre Jean-Perrin]

PURPOSE

Description of the treatment technique of stereotactic lung radiotherapy on Novalis Tx^® and prospective study of the first 100 pulmonary nodules treated at centre Jean-Perrin (France).

MATERIAL AND METHODS

From October 2012 to December 2015, 100 inoperable pulmonary nodules (62 stage I non-small-cell lung cancer and 38 metastases) of 90 patients with a mean age of 68.2 years (range: 46-89 years) were prospectively treated with dynamic arctherapy on Novalis Tx^®. Mean gross tumour and planning target volumes were respectively 6.9 cm³ (range: 0.2-31.4 cm³) and 38.7 cm³ (range: 1.7-131 cm³), which correspond to diameters equal to 2.3cm and 4.2cm. Prescribed doses to the 80% isodose line were 54Gy in three fractions for peripheral non-small-cell lung cancer, 50Gy in five fractions for central non-small-cell lung cancer and 45Gy in three fractions for lung metastases. Clinical and radiological follow-up was done every three months with RECIST criteria for efficacy and NCI-CTCAE v4 scale for toxicity. Median follow-up was 12.5 months.

RESULTS

Complete response was observed in 23.8% of cases. Local control rates were 100% and 90.7% respectively at 12 and 24 months, with 96% at 24 months for stage I non-small-cell lung cancer. Overall survival rates of patients with stage I non-small-cell lung cancer were 77.4% and 73.5% at 12 and 24 months (median overall survival was 32 months). Diffusing capacity of the lungs for carbon monoxide corrected for alveolar volume below 40% was significantly associated to a poor prognostic factor on univariate analysis (P=0.00013). At least three deaths were due to an acute respiratory failure, which correspond to about 4.8% of grade 5 radiation pneumonitis. Overall survival rate for metastatic patients were 95.2% and 59.5% respectively at 12 and 24 months (median overall survival was 25 months); 23.3% of grade 2 or less radiation pneumonitis, 7.8% of grade 2 or less radiation dermatitis, 2.2% of asymptomatic ribs fracture and 3.3% of chest pains were observed.

CONCLUSION

Stereotactic lung radiotherapy is an effective treatment for inoperable stage I non-small-cell lung cancer and lung oligometastases of well informed and selected patients. Initial respiratory state, and especially the diffusing capacity of the lungs for carbon monoxide corrected for alveolar volume, seems to be important for tolerance.

Radiation oncology in the era of precision medicine

Technological advances and clinical research over the past few decades have given radiation oncologists the capability to personalize treatments for accurate delivery of radiation dose based on clinical parameters and anatomical information. Eradication of gross and microscopic tumours with preservation of health-related quality of life can be achieved in many patients. Two major strategies, acting synergistically, will enable further widening of the therapeutic window of radiation oncology in the era of precision medicine: technology-driven improvement of treatment conformity, including advanced image guidance and particle therapy, and novel biological concepts for personalized treatment, including biomarker-guided prescription, combined treatment modalities and adaptation of treatment during its course.

Treating patients with real-time tumor tracking using the Vero gimbaled linac system: implementation and first review

PURPOSE

To report on the first clinical application of a real-time tumor tracking (RTTT) solution based on the Vero SBRT gimbaled linac system for treatment of moving tumors.

METHODS AND MATERIALS

A first group of 10 SBRT patients diagnosed with NSCLC or oligometastatic disease in lung or liver was treated with the RTTT technique. The PTV volumes and OAR exposure were benchmarked against the widely used ITV approach. Based on data acquired during execution of RTTT treatments, a first review was performed of the process.

RESULTS

The 35% PTV volume reduction with RTTT of the studied single lesions SBRT irradiations of small target volumes is expected to result in a small (<1%) reduction of lung or liver NTCP. A GTV-PTV margin of 5.0mm was applied for treatment planning of RTTT. From patient data on residual geometric uncertainties, a CTV-PTV margin of 3.2mm was calculated. Reduction of the GTV-PTV margin below 5.0mm without better understanding of biological definition of tumor boundaries was discouraged. Total treatment times were reduced to 34.4 min on average.

CONCLUSION

A considerable PTV volume reduction was achieved applying RTTT and time efficiency for respiratory correlated SBRT was reestablished with Vero RTTT.