Adaptive radiotherapy for locally advanced non-small cell lung cancer: dosimetric gain and treatment outcome prediction

Prospective imaging comparison of anatomic delineation with rapid kV cone beam CT on a novel ring gantry radiotherapy device

INTRODUCTION

A kV imager coupled to a novel, ring-gantry radiotherapy system offers improved on-board kV-cone-beam computed tomography (CBCT) acquisition time (17-40 seconds) and image quality, which may improve CT radiotherapy image-guidance and enable online adaptive radiotherapy. We evaluated whether inter-observer contour variability over various anatomic structures was non-inferior using a novel ring gantry kV-CBCT (RG-CBCT) imager as compared to diagnostic-quality simulation CT (simCT).

MATERIALS/METHODS

Seven patients undergoing radiotherapy were imaged with the RG-CBCT system at breath hold (BH) and/or free breathing (FB) for various disease sites on a prospective imaging study. Anatomy was independently contoured by seven radiation oncologists on: 1. SimCT 2. Standard C-arm kV-CBCT (CA-CBCT), and 3. Novel RG-CBCT at FB and BH. Inter-observer contour variability was evaluated by computing simultaneous truth and performance level estimation (STAPLE) consensus contours, then computing average symmetric surface distance (ASSD) and Dice similarity coefficient (DSC) between individual raters and consensus contours for comparison across image types.

RESULTS

Across 7 patients, 18 organs-at-risk (OARs) were evaluated on 27 image sets. Both BH and FB RG-CBCT were non-inferior to simCT for inter-observer delineation variability across all OARs and patients by ASSD analysis (p < 0.001), whereas CA-CBCT was not (p = 0.923). RG-CBCT (FB and BH) also remained non-inferior for abdomen and breast subsites compared to simCT on ASSD analysis (p < 0.025). On DSC comparison, neither RG-CBCT nor CA-CBCT were non-inferior to simCT for all sites (p > 0.025).

CONCLUSIONS

Inter-observer ability to delineate OARs using novel RG-CBCT images was non-inferior to simCT by the ASSD criterion but not DSC criterion.

The critical components for effective adaptive radiotherapy in patients with unresectable non-small-cell lung cancer: who, when and how

Adaptive radiotherapy (ART) is a new radiotherapy technology based on image-guided radiation therapy technology, used to avoid radiation overexposure to residual tumors and the surrounding normal tissues. Tumors undergoing the same radiation doses and modes can occur unequal shrinkage due to the variation of response times to radiation doses in different patients. To perform ART effectively, eligible patients with a high probability of benefits from ART need to be identified. Confirming the precise timetable for ART in every patient is another urgent problem to be resolved. Moreover, the outcomes of ART are different depending on the various image guidance used. This review discusses 'who, when and how' as the three key factors involved in the most effective implementation for the management of ART.

Adaptive carbon ion radiotherapy for locally advanced non-small cell lung cancer: Organ-sparing potential and target coverage

BACKGROUND

The dose distribution of carbon ion radiotherapy (CIRT) for locally advanced non-small cell lung cancer (LANSCLC) is highly sensitive to anatomical changes.

PURPOSE

To demonstrate the dosimetric benefits of adaptive CIRT for LANSCLC and compare the differences between patients with and without adaptive plans based on dosimetry and clinical effect factors.

MATERIALS AND METHODS

Of the 98 patients with LANSCLC receiving CIRT, 31 patients underwent replanning following re-evaluations that revealed changes that would have compromised the dose coverage of the target volume or violated dose constraints. Dosimetric parameters and clinical factors were compared between patients with and without adaptive plans. Multivariate analysis identified factors influencing the adaptive planning.

RESULTS

The median number of fractions delivered using adaptive plans was eight (range: 2-18). Adaptive plans ensured target coverage, and the maximum spinal cord dose was significantly decreased (p = 0.02). The median reduction in the maximum spinal cord dose was 10.4 Gy (relative biological effectiveness). Patients with adaptive plans had larger tumor volumes (p < 0.001); the median initial internal gross tumor volumes (iGTVs) of patients with adaptive and nonadaptive plans were 125.9 and 49.79 cm3 , respectively. Tumor volumes of patients with adaptive plans were altered to a greater extent (p < 0.001); the median absolute percentage of volume changes in patients in the adaptive and in nonadaptive groups were 20.76% and 3.63%, respectively, while the median movements of iGTV centers were 5.75 and 2.44 mm, respectively. Binary logistic regression analysis revealed that the iGTV volume change and iGTV center movements were significantly different between the groups.

CONCLUSIONS

An adaptive plan can effectively ensure target area coverage and protect normal tissues, especially in patients with large tumor volumes and substantial changes. iGTV volume changes and iGTV center movements are the main factors influencing adaptive planning. Weekly simulation computed tomography scans are necessary for treatment evaluation in patients with LANSCLC treated with CIRT.

Adaptive Radiation Therapy in the Treatment of Lung Cancer: An Overview of the Current State of the Field

Lung cancer treatment is constantly evolving due to technological advances in the delivery of radiation therapy. Adaptive radiation therapy (ART) allows for modification of a treatment plan with the goal of improving the dose distribution to the patient due to anatomic or physiologic deviations from the initial simulation. The implementation of ART for lung cancer is widely varied with limited consensus on who to adapt, when to adapt, how to adapt, and what the actual benefits of adaptation are. ART for lung cancer presents significant challenges due to the nature of the moving target, tumor shrinkage, and complex dose accumulation because of plan adaptation. This article presents an overview of the current state of the field in ART for lung cancer, specifically, probing topics of: patient selection for the greatest benefit from adaptation, models which predict who and when to adapt plans, best timing for plan adaptation, optimized workflows for implementing ART including alternatives to re-simulation, the best radiation techniques for ART including magnetic resonance guided treatment, algorithms and quality assurance, and challenges and techniques for dose reconstruction. To date, the clinical workflow burden of ART is one of the major reasons limiting its widespread acceptance. However, the growing body of evidence demonstrates overwhelming support for reduced toxicity while improving tumor dose coverage by adapting plans mid-treatment, but this is offset by the limited knowledge about tumor control. Progress made in predictive modeling of on-treatment tumor shrinkage and toxicity, optimizing the timing of adaptation of the plan during the course of treatment, creating optimal workflows to minimize staffing burden, and utilizing deformable image registration represent ways the field is moving toward a more uniform implementation of ART.

Early prediction of tumour-response to radiotherapy in NSCLC patients

Objective. In this study we developed an automatic method to predict tumour volume and shape in weeks 3 and 4 of radiotherapy (RT), using cone-beam computed tomography (CBCT) scans acquired up to week 2, allowing identification of large tumour changes.Approach. 240 non-small cell lung cancer (NSCLC) patients, treated with 55 Gy in 20 fractions, were collected. CBCTs were rigidly registered to the planning CT. Intensity values were extracted in each voxel of the planning target volume across all CBCT images from days 1, 2, 3, 7 and 14. For each patient and in each voxel, four regression models were fitted to voxel intensity; applying linear, Gaussian, quadratic and cubic methods. These models predicted the intensity value for each voxel in weeks 3 and 4, and the tumour volume found by thresholding. Each model was evaluated by computing the root mean square error in pixel value and structural similarity index metric (SSIM) for all patients. Finally, the sensitivity and specificity to predict a 30% change in volume were calculated for each model.Main results. The linear, Gaussian, quadratic and cubic models achieved a comparable similarity score, the average SSIM for all patients was 0.94, 0.94, 0.90, 0.83 in week 3, respectively. At week 3, a sensitivity of 84%, 53%, 90% and 88%, and specificity of 99%, 100%, 91% and 42% were observed for the linear, Gaussian, quadratic and cubic models respectively. Overall, the linear model performed best at predicting those patients that will benefit from RT adaptation. The linear model identified 21% and 23% of patients in our cohort with more than 30% tumour volume reduction to benefit from treatment adaptation in weeks 3 and 4 respectively.Significance. We have shown that it is feasible to predict the shape and volume of NSCLC tumours from routine CBCTs and effectively identify patients who will respond to treatment early.

Improved adaptive radiotherapy to adjust for anatomical alterations during curative treatment for locally advanced lung cancer

Anatomical changes during chemoradiation for lung cancer may decrease dose to the target or increase dose to organs at risk. To assess our ability to identify clinically significant anatomical alterations, we followed 67 lung cancer patients by daily cone-beam CT scans to ensure correct patient positioning and observe anatomical alterations. We also re-calculated the original dose distribution on a planned control CT scan obtained halfway during the treatment course to identify anatomical changes that potentially affected doses to the target or organs at risk. Of 66 patients who completed the treatment, 12 patients needed adaptation, two patients were adapted twice. We conclude that daily cone-beam CT and routines at the treatment machine discover relevant anatomical changes during curative radiotherapy for patients with lung cancer without additional imaging.

A method for predictive modeling of tumor regression for lung adaptive radiotherapy

PURPOSE

The purpose of this work is to create a decision support methodology to predict when patients undergoing radiotherapy treatment for locally advanced lung cancer would potentially benefit from adaptive radiotherapy. The proposed methodology seeks to eliminate the manual subjective review by developing an automated statistical learning model to predict when tumor regression would trigger implementation of adaptive radiotherapy based on quantified anatomic changes observed in individual patients on-treatment cone beam computed tomographies (CTs). This proposed process seeks to improve the efficacy and efficiency of both the existing manual and automated adaptive review processes for locally advanced stage III lung cancer.

METHODS

A predictive algorithm was developed as a decision support tool to determine the potential utility of mid-treatment adaptive radiotherapy based on anatomic changes observed on 1158 daily CBCT images across 43 patients. The anatomic changes on each axial slice within specified regions-of-interest were quantified into a single value utilizing imaging similarity criteria comparing the daily CBCT to the initial simulation CT. The range of the quantified metrics for each fraction across all axial slices are reduced to specified quantiles, which are used as the predictive input to train a logistic regression algorithm. A "ground-truth" of the need for adaptive radiotherapy based on tumor regression was evaluated systematically on each of the daily CBCTs and used as the classifier in the logistic regression algorithm. Accuracy of the predictive model was assessed utilizing both a tenfold cross validation and an independent validation dataset, with the sensitivity, specificity, and fractional accuracy compared to the ground-truth.

RESULTS

The sensitivity and specificity for the individual daily fractions ranged from 87.9%-94.3% and 91.9%-98.6% for a probability threshold of 0.2-0.5, respectively. The corresponding average treatment fraction difference between the model predictions and assessed ART "ground-truth" ranged from -2.25 to -0.07 fractions, with the model predictions consistently predicting the potential need for ART earlier in the treatment course. By initially utilizing a lower probability threshold, the higher sensitivity minimizes the chance of false negative by alerting the clinician to review a higher number of questionable cases.

CONCLUSIONS

The proposed methodology accurately predicted the first fraction at which individual patients may benefit from ART based on quantified anatomic changes observed in the on-treatment volumetric imaging. The generalizability of the proposed method has potential to expand to additional modes of adaptive radiotherapy for lung cancer patients with observed underlying anatomic changes.

Adaptive intensity-modulated radiotherapy with simultaneous integrated boost for stage III non-small cell lung cancer: Is a routine adaptation beneficial?

PURPOSE

Tumor and anatomical changes during radiotherapy have been observed in stage III non-small cell lung cancer (NSCLC) from many previous studies. We hypothesized that a routinely scheduled adaptive radiotherapy would have clinical important dose benefits to lower the risk of toxicities, without increasing the tumor recurrences.

METHODS

We retrospectively reviewed 92 consecutive patients with inoperable stage III NSCLC between November 2017 and March 2019. All eligible patients should received simultaneously integrated boost (SIB) using intensity-modulated radiation therapy (IMRT). A mid-treatment CT simulation and a new adapted plan were routinely given after the first 20 fractions. The organs at risk (OARs) were delineated per RTOG 1106 atlas. Dose-volume histograms were quantitatively compared between the initial and composite adaptive plans. Logistic regression was applied to analyze the dose-response relationship. Clinical endpoints included acute symptomatic radiation pneumonitis (RP2) and esophagitis (RE2), local and regional tumor control, and progression-free survival (PFS).

RESULTS

Sixty-four eligible patients received adaptive SIB-IMRT were consecutively included. The GTVs reduced by a median of -38.2% after 42 to 44 Gy in 20 fractions of radiotherapy. By adapting to tumor and anatomical changes, dosimetric parameters of OARs decreased significantly. The mean lung dose decreased by an average of -74.8 cGy, and mean esophagus dose was lower by 183.1 cGy. We found grade 2 or higher acute RP in 11 patients (17.2%), and RE2 in 28 patients (43.8%). Commonly used lung and esophagus dose metrics were significantly associated with RP2 and RE2. The adaptation could reduce RP2 probability by 3%, and RE2 risk by 5%. Subgroups with higher OARs dose or larger tumor shrinkage may get more dose and toxicities benefits. The estimated median PFS was 12.5 months from the start of radiotherapy.

CONCLUSIONS

We demonstrated that the routinely adaptive SIB-IMRT strategy could significantly reduce the dose to surrounding normal tissues, potentially lower the associated acute RP and RE, without increasing the risk of tumor recurrences.

Cone-Beam-CT Guided Adaptive Radiotherapy for Locally Advanced Non-small Cell Lung Cancer Enables Quality Assurance and Superior Sparing of Healthy Lung

Purpose

To evaluate the potential of cone-beam-CT (CB-CT) guided adaptive radiotherapy (ART) for locally advanced non-small cell lung cancer (NSCLC) for sparing of surrounding organs-at-risk (OAR).

Materials and Methods

In 10 patients with locally advanced NSCLC, daily CB-CT imaging was acquired during radio- (n = 4) or radiochemotherapy (n = 6) for simulation of ART. Patients were treated with conventionally fractionated intensity-modulated radiotherapy (IMRT) with total doses of 60–66 Gy (pPlan) (311 fraction CB-CTs). OAR were segmented on every daily CB-CT and the tumor volumes were modified weekly depending on tumor changes. Doses actually delivered were recalculated on daily images (dPlan), and voxel-wise dose accumulation was performed using a deformable registration algorithm. For simulation of ART, treatment plans were adapted using the new contours and re-optimized weekly (aPlan).

Results

CB-CT showed continuous tumor regression of 1.1 ± 0.4% per day, leading to a residual gross tumor volume (GTV) of 65.3 ± 13.4% after 6 weeks of radiotherapy (p = 0.005). Corresponding PTVs decreased to 83.7 ± 7.8% (p = 0.005). In the actually delivered plans (dPlan), both conformity (p = 0.005) and homogeneity (p = 0.059) indices were impaired compared to the initial plans (pPlan). This resulted in higher actual lung doses than planned: V_20Gy was 34.6 ± 6.8% instead of 32.8 ± 4.9% (p = 0.066), mean lung dose was 19.0 ± 3.1 Gy instead of 17.9 ± 2.5 Gy (p = 0.013). The generalized equivalent uniform dose (gEUD) of the lung was 18.9 ± 3.1 Gy instead of 17.8 ± 2.5 Gy (p = 0.013), leading to an increased lung normal tissue complication probability (NTCP) of 15.2 ± 13.9% instead of 9.6 ± 7.3% (p = 0.017). Weekly plan adaptation enabled decreased lung V_20Gy of 31.6 ± 6.2% (−3.0%, p = 0.007), decreased mean lung dose of 17.7 ± 2.9 Gy (−1.3 Gy, p = 0.005), and decreased lung gEUD of 17.6 ± 2.9 Gy (−1.3 Gy, p = 0.005). Thus, resulting lung NTCP was reduced to 10.0 ± 9.5% (−5.2%, p = 0.005). Target volume coverage represented by conformity and homogeneity indices could be improved by weekly plan adaptation (CI: p = 0.007, HI: p = 0.114) and reached levels of the initial plan (CI: p = 0.721, HI: p = 0.333).

Conclusion

IGRT with CB-CT detects continuous GTV and PTV changes. CB-CT-guided ART for locally advanced NSCLC is feasible and enables superior sparing of healthy lung at high levels of plan conformity.

Identification of patterns of tumour change measured on CBCT images in NSCLC patients during radiotherapy

In this study, we propose a novel approach to investigate changes in the visible tumour and surrounding tissues with the aim of identifying patterns of tumour change during radiotherapy (RT) without segmentation on the follow-up images. On-treatment cone-beam computed tomography (CBCT) images of 240 non-small cell lung cancer (NSCLC) patients who received 55 Gy of RT were included. CBCTs were automatically aligned onto planning computed tomography (planning CT) scan using a two-step rigid registration process. To explore density changes across the lung-tumour boundary, eight shells confined to the shape of the gross tumour volume (GTV) were created. The shells extended 6 mm inside and outside of the GTV border, and each shell is 1.5 mm thick. After applying intensity correction on CBCTs, the mean intensity was extracted from each shell across all CBCTs. Thereafter, linear fits were created, indicating density change over time in each shell during treatment. The slopes of all eight shells were clustered to explore patterns in the slopes that show how tumours change. Seven clusters were obtained, 97% of the patients were clustered into three groups. After visual inspection, we found that these clusters represented patients with little or no density change, progression and regression. For the three groups, the survival curves were not significantly different between the groups, p-value = 0.51. However, the results show that definite patterns of tumour change exist, suggesting that it may be possible to identify patterns of tumour changes from on-treatment CBCT images.

Critical review and quality-assessment of cost analyses in radiotherapy: How reliable are the data?

PURPOSE/OBJECTIVE

Health economic evaluations (HEE) are increasingly having an impact on policymakers, although the results greatly depend on the quality of the methodology used and on transparent reporting. The two main objectives of this study were to evaluate the quality of cost analyses of external beam radiotherapy (EBRT) and to assess the comprehensiveness and relevance of cost criteria defined in three validated quality-assessment instruments.

MATERIALS AND METHODS

The selection of articles was based on a previous systematic literature review of EBRT-costing studies retrieved from January 2004 to January 2015 (Period 1) in MEDLINE, Embase, and NHS-EED databases and completed in a second time period from January 2015 to November 2018 (Period 2). Three validated instruments to assess the methodology quality with the CHEC and the QHES, and the methodology with the CHEERS checklists were used. The quality was evaluated by both quantitative and qualitative analyses. The scoring robustness was examined with the Kendall coefficient of concordance and inter-class correlation coefficients.

RESULTS

In total, twenty-three articles were selected. The main geographic areas of cost analyses were Canada (n = 5), France (n = 4), and the USA (n = 4). The most commonly studied pathologies and technologies were prostate (n = 7) and head and neck cancer (n = 5) and IMRT (n = 8) and IGRT (n = 2), respectively. The mean instrument scores demonstrated a fair degree of methodological quality, with 69.7% for the CHEC, 73.6% for the QHES, as well as for the reporting quality, with 59.4% for CHEERS for Period 1 (74.4%, 71.5%, and 66.1%, respectively, for Period 2). An additional qualitative analysis per criterion revealed that certain items, essential for understanding the costing methodology and the results (e.g., the time horizon, discount rate, sensitivity analysis) were often only partially completed. Statistical analysis confirmed that the reviewers' scoring was consistent. The instruments identified the same top three articles, albeit with a degree of variation in the ranking.

CONCLUSION

Qualitative and quantitative assessment of cost analyses in EBRT exhibits a fair level of study quality in terms of the methodology and reporting transparency. The impact of cost calculations on the final HEE result appears to be underestimated, and increased transparency of the data sources and the methodologies is needed.

The Practicality of ICRU and Considerations for Future ICRU Definitions

The International Commission on Radiation Units and Measurements (ICRU) volumes are standardized volume definitions used in radiation oncology practice that have evolved over time to account for advancements in technology and radiation planning. The current definitions have strengths but also practical limitations. The main limitation is related to the process of accounting for tumor motion during treatment. As radiotherapeutic techniques become more precise, motion interplay effects and anatomical changes during treatment must be taken into account to ensure accurate and safe delivery of treatment. Adaptive replanning can help to mitigate the effect of these uncertainties and widen the therapeutic ratio by maximizing dose to the tumor and protecting critical normal structures. As adaptive replanning becomes more common, standardization of how adaptive therapy is implemented and reported will become necessary.