Serial megavoltage CT imaging during external beam radiotherapy for non–small-cell lung cancer: Observations on tumor regression during treatment

Adapt-On-Demand: A Novel Strategy for Personalized Adaptive Radiation Therapy for Locally Advanced Lung Cancer

PURPOSE

Real-time adaptation of thoracic radiation plans is compelling because offline adaptive experiences show that tumor volumes and lung anatomy can change during therapy. We present and analyze a novel adaptive-on-demand (AOD) workflow combining online adaptive radiation therapy (o-ART) on the ETHOS system with image guided radiation therapy delivery on a Halcyon unit for conventional fractionated radiation therapy of locally advanced lung cancer (LALC).

METHODS AND MATERIALS

We analyzed 26 patients with LALC treated with the AOD workflow, adapting weekly. We timed segments of the workflow to evaluate efficiency in a real-world clinic. Target coverage and organ at risk (OAR) doses were compared between adaptive plans (ADP) and nonadaptive scheduled plans (SCH). Planning robustness was evaluated by the frequency of preplanning goals achieved in ADP plans, stratified by tumor volume change.

RESULTS

The AOD workflow was achievable within 30 minutes for most radiation fractions. Over the course of therapy, we observed an average 26.6% ± 23.3% reduction in internal target volume (ITV). Despite these changes, with o-ART, ITV and planning target volume (PTV) coverage (V100%) was 99.2% and 93.9% for all members of the cohort, respectively. This represented a 2.9% and 6.8% improvement over nonadaptive plans (P < .05), respectively. For tumors that grew >10%, V100% was 93.1% for o-ART and 76.4% for nonadaptive plans, representing a median 17.2% improvement in the PTV coverage (P < .05). In these plans, critical OAR constraints were met 94.1% of the time, whereas in nonadaptive plans, this figure was 81.9%. This represented reductions of 1.32 Gy, 1.34 Gy, or 1.75 Gy in the heart, esophagus, and lung, respectively. The effect was larger when tumors had shrunk more than 10%. Regardless of tumor volume alterations, the PTV/ITV coverage was achieved for all adaptive plans. Exceptional cases, where dose constraints were not met, were due to large initial tumor volumes or tumor growth.

CONCLUSIONS

The AOD workflow is efficient and robust in responding to anatomic changes in LALC patients, providing dosimetric advantages over standard therapy. Weekly adaptation was adequate to keep pace with changes. This approach is a feasible alternative to conventional offline replanning workflows for managing anatomy changes in LALC radiation therapy.

Accelerated Hypofractionated Chemoradiation Followed by Stereotactic Ablative Radiotherapy Boost for Locally Advanced, Unresectable Non-Small Cell Lung Cancer: A Nonrandomized Controlled Trial

Importance

Intrathoracic progression remains the predominant pattern of failure in patients treated with concurrent chemoradiation followed by a consolidation immune checkpoint inhibitor for locally advanced, unresectable non-small cell lung cancer (NSCLC).

Objective

To determine the maximum tolerated dose (MTD) and use of hypofractionated concurrent chemoradiation with an adaptive stereotactic ablative radiotherapy (SABR) boost.

Design, Setting, and Participants

This was an early-phase, single-institution, radiation dose-escalation nonrandomized controlled trial with concurrent chemotherapy among patients with clinical stage II (inoperable/patient refusal of surgery) or III NSCLC (American Joint Committee on Cancer Staging Manual, seventh edition). Patients were enrolled and treated from May 2011 to May 2018, with a median patient follow-up of 18.2 months. Patients advanced to a higher SABR boost dose if dose-limiting toxic effects (any grade 3 or higher pulmonary, gastrointestinal, or cardiac toxic effects, or any nonhematologic grade 4 or higher toxic effects) occurred in fewer than 33% of the boost cohort within 90 days of follow-up. The current analyses were conducted from January to September 2023.

Intervention

All patients first received 4 Gy × 10 fractions followed by an adaptive SABR boost to residual metabolically active disease, consisting of an additional 25 Gy (low, 5 Gy × 5 fractions), 30 Gy (intermediate, 6 Gy × 5 fractions), or 35 Gy (high, 7 Gy × 5 fractions) with concurrent weekly carboplatin/paclitaxel.

Main Outcome and Measure

The primary outcome was to determine the MTD.

Results

Data from 28 patients (median [range] age, 70 [51-88] years; 16 [57%] male; 24 [86%] with stage III disease) enrolled across the low- (n = 10), intermediate- (n = 9), and high- (n = 9) dose cohorts were evaluated. The protocol-specified MTD was not exceeded. The incidences of nonhematologic acute and late (>90 days) grade 3 or higher toxic effects were 11% and 7%, respectively. No grade 3 toxic effects were observed in the intermediate-dose boost cohort. Two deaths occurred in the high-dose cohort. Two-year local control was 74.1%, 85.7%, and 100.0% for the low-, intermediate-, and high-dose cohorts, respectively. Two-year overall survival was 30.0%, 76.2%, and 55.6% for the low-, intermediate-, and high-dose cohorts, respectively.

Conclusions and Relevance

This early-phase, dose-escalation nonrandomized controlled trial showed that concurrent chemoradiation with an adaptive SABR boost to 70 Gy in 15 fractions with concurrent chemotherapy is a safe and effective regimen for patients with locally advanced, unresectable NSCLC.

Trial Registration

ClinicalTrials.gov Identifier: NCT01345851.

A qualitative study of improving megavoltage computed tomography image quality and maintaining dose accuracy using cycleGAN-based image synthesis

BACKGROUND

Due to inconsistent positioning, tumor shrinking, and weight loss during fractionated treatment, the initial plan was no longer appropriate after a few fractional treatments, and the patient will require adaptive helical tomotherapy (HT) to overcome the issue. Patients are scanned with megavoltage computed tomography (MVCT) before each fractional treatment, which is utilized for patient setup and provides information for dose reconstruction. However, the low contrast and high noise of MVCT make it challenging to delineate treatment targets and organs at risk (OAR).

PURPOSE

This study developed a deep-learning-based approach to generate high-quality synthetic kilovoltage computed tomography (skVCT) from MVCT and meet clinical dose requirements.

METHODS

Data from 41 head and neck cancer patients were collected; 25 (2995 slices) were used for training, and 16 (1898 slices) for testing. A cycle generative adversarial network (cycleGAN) based on attention gate and residual blocks was used to generate MVCT-based skVCT. For the 16 patients, kVCT-based plans were transferred to skVCT images and electron density profile-corrected MVCT images to recalculate the dose. The quantitative indices and clinically relevant dosimetric metrics, including the mean absolute error (MAE), structural similarity index measure (SSIM), peak signal-to-noise ratio (PSNR), gamma passing rates, and dose-volume-histogram (DVH) parameters (Dmax , Dmean , Dmin ), were used to assess the skVCT images.

RESULTS

The MAE, PSNR, and SSIM of MVCT were 109.6 ± 12.3 HU, 27.5 ± 1.1 dB, and 91.9% ± 1.7%, respectively, while those of skVCT were 60.6 ± 9.0 HU, 34.0 ± 1.9 dB, and 96.5% ± 1.1%. The image quality and contrast were enhanced, and the noise was reduced. The gamma passing rates improved from 98.31% ± 1.11% to 99.71% ± 0.20% (2 mm/2%) and 99.77% ± 0.18% to 99.98% ± 0.02% (3 mm/3%). No significant differences (p > 0.05) were observed in DVH parameters between kVCT and skVCT.

CONCLUSION

With training on a small data set (2995 slices), the model successfully generated skVCT with improved image quality, and the dose calculation accuracy was similar to that of MVCT. MVCT-based skVCT can increase treatment accuracy and offer the possibility of implementing adaptive radiotherapy.

A Novel Method for Evaluating Early Tumor Response Based on Daily CBCT Images for Lung SBRT

BACKGROUND

We aimed to develop a new tumor response assessment method for lung SBRT.

METHODS

In total, 132 lung cancer patients with 134 tumors who received SBRT treatment with daily CBCT were included in this study. The information about tumor size (area), contrast (contrast-to-noise ratio (CNR)), and density/attenuation (μ) was derived from the CBCT images for the first and the last fractions. The ratios of tumor area, CNR, and μ (RA, RCNR, Rμ) between the last and first fractions were calculated for comparison. The product of the three rations was defined as a new parameter (R) for assessment. Tumor response was independently assessed by a radiologist based on a comprehensive analysis of the CBCT images.

RESULTS

R ranged from 0.27 to 1.67 with a mean value of 0.95. Based on the radiologic assessment results, a receiver operation characteristic (ROC) curve with the area under the curve (AUC) of 95% was obtained and the optimal cutoff value (RC) was determined as 1.1. The results based on RC achieved a 94% accuracy, 94% specificity, and 90% sensitivity.

CONCLUSION

The results show that R was correlated with early tumor response to lung SBRT and that using R for evaluating tumor response to SBRT would be viable and efficient.

CBCT-guided adaptive radiotherapy using self-supervised sequential domain adaptation with uncertainty estimation

Adaptive radiotherapy (ART) is an advanced technology in modern cancer treatment that incorporates progressive changes in patient anatomy into active plan/dose adaption during the fractionated treatment. However, the clinical application relies on the accurate segmentation of cancer tumors on low-quality on-board images, which has posed challenges for both manual delineation and deep learning-based models. In this paper, we propose a novel sequence transduction deep neural network with an attention mechanism to learn the shrinkage of the cancer tumor based on patients' weekly cone-beam computed tomography (CBCT). We design a self-supervised domain adaption (SDA) method to learn and adapt the rich textural and spatial features from pre-treatment high-quality computed tomography (CT) to CBCT modality in order to address the poor image quality and lack of labels. We also provide uncertainty estimation for sequential segmentation, which aids not only in the risk management of treatment planning but also in the calibration and reliability of the model. Our experimental results based on a clinical non-small cell lung cancer (NSCLC) dataset with sixteen patients and ninety-six longitudinal CBCTs show that our model correctly learns weekly deformation of the tumor over time with an average dice score of 0.92 on the immediate next step, and is able to predict multiple steps (up to 5 weeks) for future patient treatments with an average dice score reduction of 0.05. By incorporating the tumor shrinkage predictions into a weekly re-planning strategy, our proposed method demonstrates a significant decrease in the risk of radiation-induced pneumonitis up to 35% while maintaining the high tumor control probability.

PARP-1 genetic polymorphism associated with radiation sensitivity of non-small cell lung cancer

About 70% of non-small cell lung cancer (NSCLC) patients require radiotherapy. However, due to the difference in radiation sensitivity, the treatment outcome may differ for the same pathology and choice of treatment. Poly (ADP-ribose) polymerase 1 (PARP-1) is a key gene responsible for DNA repair and is involved in base excision repair as well as repair of single strand break induced by ionizing radiation and oxidative damage. In order to investigate the relationship between PARP-1 gene polymorphism and radiation sensitivity in NSCLC, we collected 141 primary NSCLC patients undergoing three-dimensional conformal radiotherapy. For each case, the gross tumor volumes (GTV) before radiation and that after 40 Gy radiation were measured to calculate the tumor regression rate. TaqMan real-time polymerase chain reaction was performed to genotype the single-nucleotide polymorphisms (SNPs). Genotype frequencies for PARP-1 genotypes were 14.2% for C/C, 44.7% for C/G and 41.1% for G/G. The average tumor regression rate after 40 Gy radiation therapy was 35.1% ± 0.192. Tumor regression rate of mid-term RT of C/C genotype was 44.6% ± 0.170, which was higher than that of genotype C/G and G/G (32.4% ± 0.196 and 34.8% ± 0.188, respectively) with statistical significance (F = 3.169 p = 0.045). The higher tumor regression rate in patients with C/C genotype suggested that G allele was a protective factor against radiation therapy. Using the median tumor regression rate of 34%, we divided the entire cohort into two groups, and found that the frequency distribution of PARP-1 gene rs3219073 had significant difference between these two groups (p < 0.05). These results showed that PARP-1 gene polymorphism may affect patient radiation sensitivity and predict the efficacy of radiotherapy. It therefore presents an opportunity for developing new therapeutic targets to improve radiotherapy outcome.

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.

Can bronchoscopically implanted anchored electromagnetic transponders be used to monitor tumor position and lung inflation during deep inspiration breath-hold lung radiotherapy?

PURPOSE

To evaluate the efficacy of using bronchoscopically implanted anchored electromagnetic transponders (EMTs) as surrogates for 1) tumor position and 2) repeatability of lung inflation during deep-inspiration breath-hold (DIBH) lung radiotherapy.

METHODS

41 patients treated with either hypofractionated (HF) or conventional (CF) lung radiotherapy on an IRB approved prospective protocol using coached DIBH were evaluated for this study. Three anchored EMTs were bronchoscopically implanted into small airways near or within the tumor. DIBH treatment was gated by tracking the EMT positions. Breath-hold cone-beam-CTs (CBCTs) were acquired prior to every HF treatment or weekly for CF patients. Retrospectively, rigid registrations between each CBCT and the breath-hold planning CT were performed to match to 1) spine 2) EMTs and 3) tumor. Absolute differences in registration between EMTs and spine were analyzed to determine surrogacy of EMTs for lung inflation. Differences in registration between EMTs and tumor were analyzed to determine surrogacy of EMTs for tumor position. The stability of the EMTs was evaluated by analyzing the difference between inter-EMT displacements recorded at treatment from that of the plan for the CF patients, as well as the geometric residual (GR) recorded at the time of treatment.

RESULTS

219 CBCTs were analyzed. The average differences between EMT centroid and spine registration among all CBCTs were 0.45±0.42cm, 0.29±0.28cm, and 0.18±0.15cm in superior-inferior (SI), anterior-posterior (AP) and lateral directions, respectively. Only 59% of CBCTs had differences in registration <0.5cm for EMT centroid compared to spine, indicating that lung inflation is not reproducible from simulation to treatment. The average differences between EMT centroid and tumor registration among all CBCTs were 0.13±0.13cm, 0.14±0.13cm and 0.12±0.12cm in SI, AP and lateral directions, respectively. 95% of CBCTs resulted in <0.5cm change between EMT centroid and tumor registration, indicating that EMT positions correspond well with tumor position during treatments. Six out of the 7 recorded CF patients had average differences in inter-EMT displacements to be ≤0.26cm and average GR ≤0.22cm, indicating that the EMTs are stable throughout treatment.

CONCLUSIONS

Bronchoscopically implanted anchored EMTs are good surrogates for tumor position and are reliable for maintaining tumor position when tracked during DIBH treatment, as long as the tumor size and shape are stable. Large differences in registration between EMTs and spine for many treatments suggest that lung inflation achieved at simulation is often not reproduced. This article is protected by copyright. All rights reserved.

Adaptive MR-Guided Stereotactic Radiotherapy is Beneficial for Ablative Treatment of Lung Tumors in High-Risk Locations

PURPOSE

To explore the benefit of adaptive magnetic resonance-guided stereotactic body radiotherapy (MRgSBRT) for treatment of lung tumors in different locations with a focus on ultracentral lung tumors (ULT).

PATIENTS & METHODS

A prospective cohort of 21 patients with 23 primary and secondary lung tumors was analyzed. Tumors were located peripherally (N = 10), centrally (N = 2) and ultracentrally (N = 11, planning target volume (PTV) overlap with proximal bronchi, esophagus and/or pulmonary artery). All patients received MRgSBRT with gated dose delivery and risk-adapted fractionation. Before each fraction, the baseline plan was recalculated on the anatomy of the day (predicted plan). Plan adaptation was performed in 154/165 fractions (93.3%). Comparison of dose characteristics between predicted and adapted plans employed descriptive statistics and Bayesian linear multilevel models. The posterior distributions resulting from the Bayesian models are presented by the mean together with the corresponding 95% compatibility interval (CI).

RESULTS

Plan adaptation decreased the proportion of fractions with violated planning objectives from 94% (predicted plans) to 17% (adapted plans). In most cases, inadequate PTV coverage was remedied (predicted: 86%, adapted: 13%), corresponding to a moderate increase of PTV coverage (mean +6.3%, 95% CI: [5.3-7.4%]) and biologically effective PTV doses (BED₁₀) (BED_min: +9.0 Gy [6.7-11.3 Gy], BED_mean: +1.4 Gy [0.8-2.1 Gy]). This benefit was smaller in larger tumors (-0.1%/10 cm³ PTV [-0.2 to -0.02%/10 cm³ PTV]) and ULT (-2.0% [-3.1 to -0.9%]). Occurrence of exceeded maximum doses inside the PTV (predicted: 21%, adapted: 4%) and violations of OAR constraints (predicted: 12%, adapted: 1%, OR: 0.14 [0.04-0.44]) was effectively reduced. OAR constraint violations almost exclusively occurred if the PTV had touched the corresponding OAR in the baseline plan (18/19, 95%).

CONCLUSION

Adaptive MRgSBRT is highly recommendable for ablative treatment of lung tumors whose PTV initially contacts a sensitive OAR, such as ULT. Here, plan adaptation protects the OAR while maintaining best-possible PTV coverage.

Identification of modes of tumor regression in non-small cell lung cancer patients during radiotherapy

PURPOSE

Observed gross tumor volume (GTV) shrinkage during radiotherapy (RT) raises the question of whether to adapt treatment to changes observed on the acquired images. In the literature, two modes of tumor regression have been described: elastic and non-elastic. These modes of tumor regression will affect the safety of treatment adaptation. This study applies a novel approach, using routine cone-beam computed tomography (CBCT) and deformable image registration to automatically distinguish between elastic and non-elastic tumor regression.

METHODS

In this retrospective study, 150 locally advanced non-small cell lung cancer patients treated with 55 Gray of radiotherapy were included. First, the two modes of tumor regression were simulated. For each mode of tumor regression, one timepoint was simulated. Based on the results of simulated data, the approach used for analysis in real patients was developed. CBCTs were non-rigidly registered to the baseline CBCT using a cubic B-spline algorithm, NiftyReg. Next, the Jacobian determinants were computed from the deformation vector fields. To capture local volume changes, 10 Jacobian values were sampled perpendicular to the surface of the GTV, across the lung-tumor boundary. From the simulated data, we can distinguish elastic from non-elastic tumor regression by comparing the Jacobian values samples between 5 and 12.5 mm inside and 5 and 12.5 mm outside the planning GTV. Finally, morphometric results were compared between tumors of different histologies.

RESULTS

Most patients (92.3%) in our cohort showed stable disease in the first week of treatment and non-elastic shrinkage in the later weeks of treatment. At week 2, 125 patients (88%) showed stable disease, three patients (2.1%) disease progression, and 11 patients (8%) regression. By treatment completion, 91 patients (64%) had stable disease, one patient (0.7%) progression and 46 patients (32%) regression. A slight difference in the mode of tumor change was observed between tumors of different histologies.

CONCLUSION

Our novel approach shows that it may be possible to automatically quantify and identify global changes in lung cancer patients during RT, using routine CBCT images. Our results show that different regions of the tumor change in different ways. Therefore, careful consideration should be taken when adapting RT.

Managing tumor changes during radiotherapy using a deep learning model

PURPOSE

We propose a treatment planning framework that accounts for weekly lung tumor shrinkage using cone beam computed tomography (CBCT) images with a deep learning-based model.

METHODS

Sixteen patients with non-small-cell lung cancer (NSCLC) were selected with one planning CT and six weekly CBCTs each. A deep learning-based model was applied to predict the weekly deformation of the primary tumor based on the spatial and temporal features extracted from previous weekly CBCTs. Starting from Week 3, the tumor contour at Week N was predicted by the model based on the input from all the previous weeks (1, 2 … N - 1), and was evaluated against the manually contoured tumor using Dice coefficient (DSC), precision, average surface distance (ASD), and Hausdorff distance (HD). Information about the predicted tumor was then entered into the treatment planning system and the plan was re-optimized every week. The objectives were to maximize the dose coverage in the target region while minimizing the toxicity to the surrounding healthy tissue. Dosimetric evaluation of the target and organs at risk (heart, lung, esophagus, and spinal cord) was performed on four cases, comparing between a conventional plan (ignoring tumor shrinkage) and the shrinkage-based plan.

RESULTS

he primary tumor volumes decreased on average by 38% ± 26% during six weeks of treatment. DSCs and ASD between the predicted tumor and the actual tumor for Weeks 3, 4, 5, 6 were 0.81, 0.82, 0.79, 0.78 and 1.49, 1.59, 1.92, 2.12 mm, respectively, which were significantly superior to the score of 0.70, 0.68, 0.66, 0.63 and 2.81, 3.22, 3.69, 3.63 mm between the rigidly transferred tumors ignoring shrinkage and the actual tumor. While target coverage metrics were maintained for the re-optimized plans, lung mean dose dropped by 2.85, 0.46, 2.39, and 1.48 Gy for four sample cases when compared to the original plan. Doses in other organs such as esophagus were also reduced for some cases.

CONCLUSION

We developed a deep learning-based model for tumor shrinkage prediction. This model used CBCTs and contours from previous weeks as input and produced reasonable tumor contours with a high prediction accuracy (DSC, precision, HD, and ASD). The proposed framework maintained target coverage while reducing dose in the lungs and esophagus.

Prognostic impact of gross tumor volume during radical radiochemotherapy of locally advanced non-small cell lung cancer-results from the NCT03055715 multicenter cohort study of the Young DEGRO Trial Group

BACKGROUND

In radical radiochemotherapy (RCT) of inoperable non-small-cell lung cancer (NSCLC) typical prognostic factors include T- and N-stage, while there are still conflicting data on the prognostic relevance of gross tumor volume (GTV) and particularly its changes during RCT. The NCT03055715 study of the Young DEGRO working group of the German Society of Radiation Oncology (DEGRO) evaluated the prognostic impact of GTV and its changes during RCT.

METHODS

A total of 21 university centers for radiation oncology from five different European countries (Germany, Switzerland, Spain, Belgium, and Austria) participated in the study which evaluated n = 347 patients with confirmed (biopsy) inoperable NSCLC in UICC stage III A/B who received radical curative-intent RCT between 2010 and 2013. Patient and disease data were collected anonymously via electronic case report forms and entered into the multi-institutional RadPlanBio platform for central data analysis. GTV before RCT (initial planning CT, GTV1) and at 40-50 Gy (re-planning CT for radiation boost, GTV2) was delineated. Absolute GTV before/during RCT and relative GTV changes were correlated with overall survival as the primary endpoint. Hazard ratios (HR) of survival analysis were estimated by means of adjusted Cox regression models.

RESULTS

GTV1 was found to have a mean of 154.4 ml (95%CI: 1.5-877) and GTV2 of 106.2 ml (95% CI: 0.5-589.5), resulting in an estimated reduction of 48.2 ml (p < 0.001). Median overall survival (OS) was 18.8 months with a median of 22.1, 20.9, and 12.6 months for patients with high, intermediate, and low GTV before RT. Considering all patients, in one survival model of overall mortality, GTV2 (2.75 (1.12-6.75, p = 0.03) was found to be a stronger survival predictor than GTV1 (1.34 (0.9-2, p > 0.05). In patients with available data on both GTV1 and GTV2, absolute GTV1 before RT was not significantly associated with survival (HR 0-69, 0.32-1.49, p > 0.05) but GTV2 significantly predicted OS in a model adjusted for age, T stage, and chemotherapy, with an HR of 3.7 (1.01-13.53, p = 0.04) per 300 ml. The absolute decrease from GTV1 to GTV2 was correlated to survival, where every decrease by 50 ml reduced the HR by 0.8 (CI 0.64-0.99, p = 0.04). There was no evidence for a survival effect of the relative change between GTV1 and GTV2.

CONCLUSION

Our results indicate that independently of T stage, the re-planning GTV during RCT is a significant and superior survival predictor compared to baseline GTV before RT. Patients with a high absolute (rather than relative) change in GTV during RT show a superior survival outcome after RCT.

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.

Application of the transosseous approach for computed tomography-guided radioactive 125-iodine seed implantation for the treatment of thoracic and abdominal lymph node metastases

Aim

This study aimed to investigate the technical procedure, safety, and clinical value of the transosseous approach for computed tomography (CT)-guided radioactive 125-iodine (¹²⁵I) seed implantation for the treatment of thoracic and abdominal lymph node metastases.

Subjects and Methods

This was a retrospective study that Nine lymph node metastases in nine patients were treated in our hospital between January 2010 and August 2018. Under CT guidance, at least one puncture path was made through the transosseous approach. The seeds were planted according to the TPS. CT/MRI scans were performed every 2 months after the treatment to evaluate local therapeutic efficacy according to the Response Evaluation Criteria in Solid Tumors.

Results

The transosseous approach was successfully established in all patients. The median follow-up time was 11 months (6-36 months). At 2, 4, 6, 8, 10 and 12 months after operation, the objective effective rate and clinical benefit rate were 66.67%, 77.78%, 77.78%, 71.43%, 66.67% and 50.00%; and 88.89%, 88.89%, 88.89%, 71.43%, 66.67% and 50.00%, respectively. The survival rate of the patients at 6, 12, 18, 24, 30 and 36 months after operation was 53.00%, 26.00%, 26.00%, 13.00%, 13.00% and 13.00%, respectively.

Conclusions

The transosseous approach for CT-guided radioactive ¹²⁵I seed implantation was safe, effective, and minimally invasive for the treatment of thoracic and abdominal lymph node metastases.

Performance of Makerless Tracking for Gimbaled Dynamic Tumor Tracking

BACKGROUND AND PURPOSE

The purpose of this work is to report the workflow and the accuracy of the new markerless dynamic tumor tracking (MLDTT) method of the Vero 4DRT system introduced with ExacTrac 3.6.1.

MATERIAL AND METHODS

Phantom measurements were performed to assess the accuracy of the MLDTT algorithm by using the QA-tool which is provided by the vendor. A patient breathing curve was used as the motion trajectory of the phantom and the target positions detected by the MLDTT algorithm were compared to the defined positions. Furthermore, eight patients have been treated with MLDTT between May 2018 and July 2019. A log-file analysis is used to evaluate MLDTT treatment data.

RESULTS

The accuracy of the MLDTT detection is 0.12mm ± 0.12mm, 0.12mm ± 0.11mm, 0.20mm ± 0.21mm for the x-, y-, z-direction, respectively. These values are comparable to the accuracy of marker based DTT at the Vero system. The median treatment time was 21min 34seconds and 175kV images were acquired during treatment for monitoring the target motion.

CONCLUSION

The accuracy of the MLDTT algorithm is comparable to the marker based approach and the accuracy reported for the XSight Lung of the CyberKnife. Eight patients were treated successfully using MLDTT and the treatment times are comparable to a standard DTT treatment.

Practical Clinical Workflows for Online and Offline Adaptive Radiation Therapy

Adaptive radiotherapy emerged over 20 years ago and is now an established clinical practice in a number of organ sites. No one solution for adaptive therapy exists. Rather, adaptive radiotherapy is a process which combines multiple tools for imaging, assessment of need for adaptation, treatment planning, and quality assurance of this process. Workflow is therefore a critical aspect to ensure safe, effective, and efficient implementation of adaptive radiotherapy. In this work, we discuss the tools for online and offline adaptive radiotherapy and introduce workflow concepts for these types of adaptive radiotherapy. Common themes and differences between the workflows are introduced and controversies and areas of active research are discussed.

Incidence and evolution of imaging changes on cone-beam CT during and after radical radiotherapy for non-small cell lung cancer

BACKGROUND AND PURPOSE

Cone beam CT (CBCT) is used to improve accuracy of radical radiotherapy by adjusting treatment to the observed imaging changes. To ensure appropriate adjustment, image interpretation should precede any changes to treatment delivery. This study provides the methodology for image interpretation and the frequency and evolution of the changes in patients undergoing radical radiotherapy for localised and locally advanced non-small cell lung cancer (NSCLC).

PATIENTS AND METHODS

From December 2012 to December 2014, 250 patients with localised and locally advanced NSCLC had 2462 chest CBCT scans during the course of fractionated radical radiotherapy (RT) (3-5 daily CBCTs in the first week followed by at least weekly imaging, mean 9.5 per patient, range 1-21). All CBCT images were reviewed describing changes and their evolution using diagnostic imaging definitions and validated by an independent chest radiologist.

RESULTS

During radical RT for NSCLC 328 imaging changes were identified on CBCT in 180 (72%) patients; 104 (32%) had reduction and 41 (13%) increase in tumour size; 48 (15%) had changes in consolidations contiguous to the primary lesion, 26 (8%) non-contiguous consolidations, 43 (13%) changes in tumour cavitation, 36 (11%) pleural effusion and 30 (9%) changes in atelectasis. In 105 patients imaging changes were noted in continuity with the treated tumour of which only 41 (39%) represented tumour enlargement; others included new or enlarging adjacent consolidation (34%), and new or enlarging atelectasis (19%). The changes evolved during treatment.

CONCLUSION

Imaging changes on CBCT include real and apparent changes in tumour size and parenchymal changes which evolve during treatment. Correct image interpretation, particularly when occurring adjacent to the tumour, is essential prior to adjustment to treatment delivery.

A radiomic approach for adaptive radiotherapy in non-small cell lung cancer patients

The primary goal of precision medicine is to minimize side effects and optimize efficacy of treatments. Recent advances in medical imaging technology allow the use of more advanced image analysis methods beyond simple measurements of tumor size or radiotracer uptake metrics. The extraction of quantitative features from medical images to characterize tumor pathology or heterogeneity is an interesting process to investigate, in order to provide information that may be useful to guide the therapies and predict survival. This paper discusses the rationale supporting the concept of radiomics and the feasibility of its application to Non-Small Cell Lung Cancer in the field of radiation oncology research. We studied 91 stage III patients treated with concurrent chemoradiation and adaptive approach in case of tumor reduction during treatment. We considered 12 statistics features and 230 textural features extracted from the CT images. In our study, we used an ensemble learning method to classify patients' data into either the adaptive or non-adaptive group during chemoradiation on the basis of the starting CT simulation. Our data supports the hypothesis that a specific signature can be identified (AUC 0.82). In our experience, a radiomic signature mixing semantic and image-based features has shown promising results for personalized adaptive radiotherapy in non-small cell lung cancer.

Validating a Predictive Atlas of Tumor Shrinkage for Adaptive Radiotherapy of Locally Advanced Lung Cancer

PURPOSE

To cross-validate and expand a predictive atlas that can estimate geometric patterns of lung tumor shrinkage during radiation therapy using data from 2 independent institutions and to model its integration into adaptive radiation therapy (ART) for enhanced dose escalation.

METHODS AND MATERIALS

Data from 22 patients at a collaborating institution were obtained to cross-validate an atlas, originally created with 12 patients, for predicting patterns of tumor shrinkage during radiation therapy. Subsequently, the atlas was expanded by integrating all 34 patients. Each study patient was selected via a leave-one-out scheme and was matched with a subgroup of the remaining 33 patients based on similarity measures of tumor volume and surroundings. The spatial distribution of residual tumor was estimated by thresholding the superimposed shrinkage patterns in the subgroup. A Bayesian method was also developed to recalibrate the prediction using the tumor observed on the midcourse images. Finally, in a retrospective predictive treatment planning (PTP) study, at the initial planning stage, the predicted residual tumors were escalated to the highest achievable dose while maintaining the original prescription dose to the remainder of the tumor. The PTP approach was compared isotoxically to ART that replans with midcourse imaging and to PTP-ART with the recalibrated prediction.

RESULTS

Predictive accuracy (true positive plus true negative ratios based on predicted and actual residual tumor) were comparable across institutions, 0.71 versus 0.73, and improved to 0.74 with an expanded atlas including 2 institutions. Recalibration further improved accuracy to 0.76. PTP increased the mean dose to the actual residual tumor by an averaged 6.3Gy compared to ART.

CONCLUSION

A predictive atlas found to perform well across institutions and benefit from more diversified shrinkage patterns and tumor locations. Elevating tumoricidal dose to the predicted residual tumor throughout the entire treatment course could improve the efficacy and efficiency of treatment compared to ART with midcourse replanning.

Early tumor shrinkage served as a prognostic factor for patients with stage III non-small cell lung cancer treated with concurrent chemoradiotherapy

BACKGROUND

Lung cancer is the most common cause of cancer death. About 80% of patients are diagnosed at stage III in the non-small cell lung cancer (NSCLC). It is extremely important to understand the progression of this disease which has low survival times despite the advancing treatment modalities. We aimed to investigate the relationship between early tumor shrinkage (ETS) after initial concurrent chemoradiotherapy (C-CRT) and survival outcome in patients with stage III (NSCLC).

METHODS

A retrospective review of 103 patients with stage III NSCLC who had received C-CRT from January 2006 to October 2011 was performed. Patients were treated with systemic chemotherapy regimen of Cisplatin/Vp-16 and concurrent thoracic radiotherapy at a median dose of 66 Gy (range 60-70 Gy). All patients received a computed tomography (CT) examination before treatment. Also subsequently, chest CT scans were performed with the same imaging parameters at approximately 5 weeks after the initiation of treatment. ETS is here stratified by a decrease in tumor size ≥30% and <30% in the longest dimension of the target lesion within 5 weeks.

RESULTS

Of the 103 patients, 59 ones showed a 30% decrease in tumor size, and the rest displayed a decrease of <30%. ETS showed no significant correlation with age, T classification, N classification, histological classification, smoking status, G classification, EGFR status, or acute pulmonary toxicity. In the current retrospective clinical study, Kaplan-Meier curves showed that patients with ETS ≥ 30% had a better progression-free survival and overall survival. The univariate and multivariate Cox regression analyses indicated that ETS < 30% was associated with a significantly increased risk of cancer-related death (P < .05) in stage IIINSCLC.

CONCLUSIONS

ETS may be served as a useful prognostic factor to predict the outcome of stage III NSCLC patients treated with CCRT.

Utilization of a hybrid finite-element based registration method to quantify heterogeneous tumor response for adaptive treatment for lung cancer patients

Tumor response to radiation treatment (RT) can be evaluated from changes in metabolic activity between two positron emission tomography (PET) images. Activity changes at individual voxels in pre-treatment PET images (PET1), however, cannot be derived until their associated PET-CT (CT1) images are appropriately registered to during-treatment PET-CT (CT2) images. This study aimed to investigate the feasibility of using deformable image registration (DIR) techniques to quantify radiation-induced metabolic changes on PET images. Five patients with non-small-cell lung cancer (NSCLC) treated with adaptive radiotherapy were considered. PET-CTs were acquired two weeks before RT and 18 fractions after the start of RT. DIR was performed from CT1 to CT2 using B-Spline and diffeomorphic Demons algorithms. The resultant displacements in the tumor region were then corrected using a hybrid finite element method (FEM). Bitmap masks generated from gross tumor volumes (GTVs) in PET1 were deformed using the four different displacement vector fields (DVFs). The conservation of total lesion glycolysis (TLG) in GTVs was used as a criterion to evaluate the quality of these registrations. The deformed masks were united to form a large mask which was then partitioned into multiple layers from center to border. The averages of SUV changes over all the layers were 1.0  ±  1.3, 1.0  ±  1.2, 0.8  ±  1.3, 1.1  ±  1.5 for the B-Spline, B-Spline  +  FEM, Demons and Demons  +  FEM algorithms, respectively. TLG changes before and after mapping using B-Spline, Demons, hybrid-B-Spline, and hybrid-Demons registrations were 20.2%, 28.3%, 8.7%, and 2.2% on average, respectively. Compared to image intensity-based DIR algorithms, the hybrid FEM modeling technique is better in preserving TLG and could be useful for evaluation of tumor response for patients with regressing tumors.

Dosimetric benefit of adaptive radiotherapy in the neoadjuvant management of canine and feline thymoma-An exploratory case series

While surgery is the treatment of choice for thymomas, complete excision is not possible in a significant proportion of cases. For these patients, radiotherapy can be used as neoadjunctive, post-operative adjunctive or sole therapy. During radiotherapy, rapid biological clearance of tumour cells is often observed, requiring adaptation of the treatment plan. Adaptive radiation therapy (RT) is a dynamic process, whereby the treatment plan is altered throughout the treatment course due to changes in morphologic, functional or positioning changes. With the hypothesis, that individually adapted replanning will massively reduce the dose to organs at risk (OAR) in a fast-changing environment such as a rapidly responding thymoma, the dosimetric impact of adaptive treatment planning in 5 patients with large thymoma was measured. In all patients rapid tumour-shrinkage of the gross tumour volume was observed after 1 week of therapy, with a mean shrinkage of 31.0% ± 15.2%, or a tumour regression of 5.2% per day. In consequence, there was a considerable change in position of organs such as heart and lung, both of them moving cranially into the high dose area upon tumour regression. After mid-therapy replanning, the dose to OAR was significantly reduced, with -18.2% in the mean heart dose and -27.9% in the V20 lung dose. Adaptive planning led to a significantly reduced radiation dose and hence protection of OAR for these patients. It can be concluded that adaptive replanning should be considered for canine and feline thymoma patients receiving fractionated RT.

Anatomic, functional and molecular imaging in lung cancer precision radiation therapy: treatment response assessment and radiation therapy personalization

This article reviews key imaging modalities for lung cancer patients treated with radiation therapy (RT) and considers their actual or potential contributions to critical decision-making. An international group of researchers with expertise in imaging in lung cancer patients treated with RT considered the relevant literature on modalities, including computed tomography (CT), magnetic resonance imaging (MRI) and positron emission tomography (PET). These perspectives were coordinated to summarize the current status of imaging in lung cancer and flag developments with future implications. Although there are no useful randomized trials of different imaging modalities in lung cancer, multiple prospective studies indicate that management decisions are frequently impacted by the use of complementary imaging modalities, leading both to more appropriate treatments and better outcomes. This is especially true of ¹⁸F-fluoro-deoxyglucose (FDG)-PET/CT which is widely accepted to be the standard imaging modality for staging of lung cancer patients, for selection for potentially curative RT and for treatment planning. PET is also more accurate than CT for predicting survival after RT. PET imaging during RT is also correlated with survival and makes response-adapted therapies possible. PET tracers other than FDG have potential for imaging important biological process in tumors, including hypoxia and proliferation. MRI has superior accuracy in soft tissue imaging and the MRI Linac is a rapidly developing technology with great potential for online monitoring and modification of treatment. The role of imaging in RT-treated lung cancer patients is evolving rapidly and will allow increasing personalization of therapy according to the biology of both the tumor and dose limiting normal tissues.

European Organization for Research and Treatment of Cancer (EORTC) recommendations for planning and delivery of high-dose, high precision radiotherapy for lung cancer

PURPOSE

To update literature-based recommendations for techniques used in high-precision thoracic radiotherapy for lung cancer, in both routine practice and clinical trials.

METHODS

A literature search was performed to identify published articles that were considered clinically relevant and practical to use. Recommendations were categorised under the following headings: patient positioning and immobilisation, Tumour and nodal changes, CT and FDG-PET imaging, target volumes definition, radiotherapy treatment planning and treatment delivery. An adapted grading of evidence from the Infectious Disease Society of America, and for models the TRIPOD criteria, were used.

RESULTS

Recommendations were identified for each of the above categories.

CONCLUSION

Recommendations for the clinical implementation of high-precision conformal radiotherapy and stereotactic body radiotherapy for lung tumours were identified from the literature. Techniques that were considered investigational at present are highlighted.

Local Control and Toxicity of Adaptive Radiotherapy Using Weekly CT Imaging: Results from the LARTIA Trial in Stage III NSCLC

INTRODUCTION

Anatomical change of tumor during radiotherapy contributes to target missing. However, in the case of tumor shrinkage, adaptation of volume could result in an increased incidence of recurrence in the area of target reduction. This study aims to investigate the incidence of failure of the adaptive approach and, in particular, the risk for local recurrence in the area excluded after replanning.

METHODS

In this prospective study, patients with locally advanced NSCLC treated with concomitant chemoradiation underwent weekly chest computed tomography simulation during treatment. In the case of tumor shrinkage, a new tumor volume was delineated and a new treatment plan outlined (replanning). Toxicity was evaluated with the Radiation Therapy Oncology Group/European Organization for Research and Treatment of Cancer scale. Patterns of failures were classified as in field (dimensional and/or metabolic progression within the replanning planning target volume [PTV]), marginal (recurrence in initial the PTV excluded from the replanning PTV), and out of field (recurrence outside the initial PTV).

RESULTS

Replanning was outlined in 50 patients selected from a total of 217 patients subjected to weekly simulation computed tomography in our center from 2012 to 2014. With a median follow-up of 20.5 months, acute grade 3 or higher pulmonary and esophageal toxicity were reported in 2% and 4% of cases and late toxicity in 4% and 2%, respectively. Marginal relapse was recorded in 6% of patients, and 20% and 4% of patients experienced in-field and out-of-field local failure, respectively.

CONCLUSIONS

The reduced toxicity and the documented low rate of marginal failures make the adaptive approach a modern option for future randomized studies. The best scenario to confirm its application is probably in neoadjuvant chemoradiation trials.

Audiovisual biofeedback guided breath-hold improves lung tumor position reproducibility and volume consistency

Purpose

Respiratory variation can increase the variability of tumor position and volume, accounting for larger treatment margins and longer treatment times. Audiovisual biofeedback as a breath-hold technique could be used to improve the reproducibility of lung tumor positions at inhalation and exhalation for the radiation therapy of mobile lung tumors. This study aimed to assess the impact of audiovisual biofeedback breath-hold (AVBH) on interfraction lung tumor position reproducibility and volume consistency for respiratory-gated lung cancer radiation therapy.

Methods

Lung tumor position and volume were investigated in 9 patients with lung cancer who underwent a breath-hold training session with AVBH before 2 magnetic resonance imaging (MRI) sessions. During the first MRI session (before treatment), inhalation and exhalation breath-hold 3-dimensional MRI scans with conventional breath-hold (CBH) using audio instructions alone and AVBH were acquired. The second MRI session (midtreatment) was repeated within 6 weeks after the first session. Gross tumor volumes (GTVs) were contoured on each dataset. CBH and AVBH were compared in terms of tumor position reproducibility as assessed by GTV centroid position and position range (defined as the distance of GTV centroid position between inhalation and exhalation) and tumor volume consistency as assessed by GTV between inhalation and exhalation.

Results

Compared with CBH, AVBH improved the reproducibility of interfraction GTV centroid position by 46% (P = .009) from 8.8 mm to 4.8 mm and GTV position range by 69% (P = .052) from 7.4 mm to 2.3 mm. Compared with CBH, AVBH also improved the consistency of intrafraction GTVs by 70% (P = .023) from 7.8 cm³ to 2.5 cm³.

Conclusions

This study demonstrated that audiovisual biofeedback can be used to improve the reproducibility and consistency of breath-hold lung tumor position and volume, respectively. These results may provide a pathway to achieve more accurate lung cancer radiation treatment in addition to improving various medical imaging and treatments by using breath-hold procedures.

Association of Topoisomerase II (TOP2A) and Dual-Specificity Phosphatase 6 (DUSP6) Single Nucleotide Polymorphisms with Radiation Treatment Response and Prognosis of Lung Cancer in Han Chinese

Background

Mutations of DNA topoisomerase II (TOP2A) are associated with chemotherapy resistance, whereas dual-specificity phosphatase 6 (DUSP6) negatively regulates members of the mitogen-activated protein (MAP) kinase superfamily to control cell proliferation. This study assessed TOP2A and DUSP6 single nucleotide polymorphisms (SNPs) in non-small cell lung cancer (NSCLC) patients for association with chemoradiotherapy responses and prognosis.

Material/Methods

A total of 140 Chinese patients with histologically confirmed NSCLC were enrolled and subjected to genotyping of TOP2A rs471692 and DUSP6 rs2279574 using Taqman PCR. An independent sample t test was used to analyze differences in tumor regression after radiotherapy versus SNP risk factors. Kaplan-Meier curves analyzed overall survival, followed by the log-rank test and Cox proportional hazard models.

Results

There were no significant associations of TOP2A rs471692 and DUSP6 rs2279574 polymorphisms or clinicopathological variables with response to chemoradiotherapy (p>0.05). Comparing overall survival of 87 patients with stage I–III NSCLC treated with radiotherapy or chemoradiotherapy to clinicopathological variables, the data showed that tumor regression, weight loss, clinical stage, and cigarette smoking were independent prognostic predictors (p=0.009, 0.043, 0.004, and 0.025, respectively). Tumor regression rate >0.34 was associated with patent survival versus tumor regression rate ≤0.34 (p=0.007).

Conclusions

TOP2A rs471692 and DUSP6 rs2279574 SNPs were not associated with chemoradiotherapy response, whereas tumor regression, weight loss, clinical stage, and cigarette smoking were independent prognostic predictors for these Chinese patients with NSCLC.

Late-Course Adaptive Adjustment Based on Metabolic Tumor Volume Changes during Radiotherapy May Reduce Radiation Toxicity in Patients with Non-Small Cell Lung Cancer

To reduce the high risk of radiation toxicity and enhance the quality of life of patients with non-small cell lung cancer (NSCLC), we quantified the metabolic tumor volumes (MTVs) from baseline to the late-course of radiotherapy (RT) by fluorodeoxyglucose positron emission tomography computerized tomography (FDG PET-CT) and discussed the potential benefit of late-course adaptive plans rather than original plans by dose volume histogram (DVH) comparisons. Seventeen patients with stage II-III NSCLC who were treated with definitive conventionally fractionated RT were eligible for this prospective study. FDG PET-CT scans were acquired within 1 week before RT (pre-RT) and at approximately two-thirds of the total dose during-RT (approximately 40 Gy). MTVs were taken as gross tumor volumes (GTVs) that included the primary tumor and any involved hilar or mediastinal lymph nodes. An original plan based on the baseline MTVs and adaptive plans based on observations during-RT MTVs were generated for each patient. The DVHs for lung, heart, esophagus and spinal cord were compared between the original plans and composite plans at 66 Gy. At the time of approximately 40 Gy during-RT, MTVs were significantly reduced in patients with NSCLC (pre-RT 136.2±82.3 ml vs. during-RT 64.7±68.0 ml, p = 0.001). The composite plan of the original plan at 40 Gy plus the adaptive plan at 26 Gy resulted in better DVHs for all the organs at risk that were evaluated compared to the original plan at 66 Gy (p<0.05), including V₅, V₁₀, V₁₅, V₂₀, V₂₅, V₃₀ and the mean dose of total lung, V₁₀, V₂₀, V₃₀, V₄₀, V₅₀, V₆₀ and the mean dose of heart, V₃₅, V₄₀, V₅₀, V_55, V₆₀, the maximum dose and mean dose of the esophagus, and the maximum dose of the spinal-cord. PET-MTVs were reduced significantly at the time of approximately 40 Gy during-RT. Late course adaptive radiotherapy may be an effective way to reduce the dose volume to the organs at risk, thus reducing radiation toxicity in patients with NSCLC.

A geometric atlas to predict lung tumor shrinkage for radiotherapy treatment planning

To develop a geometric atlas that can predict tumor shrinkage and guide treatment planning for non-small-cell lung cancer. To evaluate the impact of the shrinkage atlas on the ability of tumor dose escalation. The creation of a geometric atlas included twelve patients with lung cancer who underwent both planning CT and weekly CBCT for radiotherapy planning and delivery. The shrinkage pattern from the original pretreatment to the residual posttreatment tumor was modeled using a principal component analysis, and used for predicting the spatial distribution of the residual tumor. A predictive map was generated by unifying predictions from each individual patient in the atlas, followed by correction for the tumor's surrounding tissue distribution. Sensitivity, specificity, and accuracy of the predictive model for classifying voxels inside the original gross tumor volume were evaluated. In addition, a retrospective study of predictive treatment planning (PTP) escalated dose to the predicted residual tumor while maintaining the same level of predicted complication rates for a clinical plan delivering uniform dose to the entire tumor. The effect of uncertainty on the predictive model's ability to escalate dose was also evaluated. The sensitivity, specificity and accuracy of the predictive model were 0.73, 0.76, and 0.74, respectively. The area under the receiver operating characteristic curve for voxel classification was 0.87. The Dice coefficient and mean surface distance between the predicted and actual residual tumor averaged 0.75, and 1.6 mm, respectively. The PTP approach allowed elevation of PTV D95 and mean dose to the actual residual tumor by 6.5 Gy and 10.4 Gy, respectively, relative to the clinical uniform dose approach. A geometric atlas can provide useful information on the distribution of resistant tumors and effectively guide dose escalation to the tumor without compromising the organs at risk complications. The atlas can be further refined by using more patient data sets.

Potential for adaptive dose escalation in radiotherapy for patients with locally advanced non-small-cell lung cancer in a low mid income setting

OBJECTIVE

To evaluate the effect of tumour volume regression on adaptive treatment planning, reduction in doses to organs at risk (OARs) and dose escalation.

METHODS

20 patients undergoing radical chemoradiotherapy were imaged in the fifth week of radiotherapy (CT_45) to evaluate differences in tumour volume regression between concurrent and sequential chemoradiotherapy. Replanning was carried out in the CT_45 in those with >20% regression (n = 10) and evaluated for change in target coverage indices (the coverage index and external volume index) and doses to the OAR [mean lung dose, V₂₀ and V₅ of whole and ipsilateral lung (MLD_WL, V_20WL, V_5WL, MLD_IL, V_20IL, V_5IL); mean oesophagus dose, V_50oesophagus; and maximum spinal cord doses]. The feasibility of maximum dose escalation was explored keeping the limit of the OAR below their tolerance limits.

RESULTS

Tumour regression was higher with concurrent chemoradiotherapy as compared with sequential chemoradiotherapy (p = 0.02). With the adaptive plan, the mean coverage index improved from 0.96 (±0.14) to 1.29 (±0.36), the mean external volume index changed from 1.39(±0.60) to 1.41(±0.56) and the reduction in doses to the OARs were MLD_WL 10.6%, V_20WL 1.3%, V_5WL 1.2%, MLD_IL 6.6%, V_20IL 1.5%, V_5IL 2.3%, mean oesophagus dose 7%, V_50oesophagus 31% and maximum cord dose 0.35%. Dose escalation was possible in four patients in CT_45.

CONCLUSION

There is 35% reduction in tumour volume with chemoradiotherapy at 45 Gy which allows improvement in conformality, reduction in doses to the OARs and dose escalation in 40% of patients. Advances in knowledge: This article emphasizes that adaptive planning with a single diagnostic scan at 45 Gy has the potential for improvement of radiotherapy planning indices, dose escalation while respecting the dose to the OAR. This simple strategy can be helpful in radiotherapy planning upto 60 Gy in 40% of the patients of locally advanced non-small-cell lung cancer in countries with limited resources.

Effect of deformable registration uncertainty on lung SBRT dose accumulation

PURPOSE

Deformable image registration (DIR) plays an important role in dose accumulation, such as incorporating breathing motion into the accumulation of the delivered dose based on daily 4DCBCT images. However, it is not yet well understood how the uncertainties associated with DIR methods affect the dose calculations and resulting clinical metrics. The purpose of this study is to evaluate the impact of DIR uncertainty on the clinical metrics derived from its use in dose accumulation.

METHODS

A biomechanical model based DIR method and a biomechanical-intensity-based hybrid method, which reduced the average registration error by 1.6 mm, were applied to ten lung cancer patients. A clinically relevant dose parameter [minimum dose to 0.5 cm(3) (Dmin)] was calculated for three dose scenarios using both algorithms. Dose scenarios included static (no breathing motion), predicted (breathing motion at the time of planning), and total accumulated (interfraction breathing motion). The relationship between the dose parameter and a combination of DIR uncertainty metrics, tumor volume, and dose heterogeneity of the plan was investigated.

RESULTS

Depending on the dose heterogeneity, tumor volume, and DIR uncertainty, in over 50% of the patients, differences greater than 1.0 Gy were observed in the Dmin of the tumor in the static dose calculation on exhale phase of the 4DCT. Such differences were due to the errors in propagating the tumor contours from the reference planning 4DCT phase onto a subsequent 4DCT phase using each DIR algorithm and calculating the dose on that phase. The differences in predicted dose were more subtle when breathing motion was modeled explicitly at the time of planning with only one patient exhibiting a greater than 1.0 Gy difference in Dmin. Dmin differences of up to 2.5 Gy were found in the total accumulated delivered dose due to difference in quantifying the interfraction variations. Such dose uncertainties could potentially be clinically significant.

CONCLUSIONS

Reductions in average uncertainty in DIR algorithms by 1.6 mm may have a clinically significant impact on the decision-making metrics used in dose planning and dose accumulation assessment.

Image guided volumetric response during chemoradiotherapy for head and neck squamous cell carcinoma as a predictor of disease outcomes

PURPOSE

The goal of this study was to correlate volumetric image guided disease response to clinical outcomes in patients receiving chemoradiation therapy (CRT) for locally advanced head and neck squamous cell carcinoma (HNSCC).

MATERIALS AND METHODS

Thirty four patients completing definitive CRT for locally advanced HNSCC with megavoltage computed tomography (MVCT) guided tomotherapy IMRT were retrospectively reviewed for volumetric response. Grossly identifiable primary tumor (PT) and nodal disease (ND) response was evaluated by weekly MVCT regression. Percent end-of-treatment (EOT) residual volumes and regression rates were correlated with risk of local failure (LF), progression free survival (PFS), and overall survival (OS).

RESULTS

A total of 7 LFs were identified in 6 patients at a median follow-up of 8months. The mean percent EOT residual volumes for PT and ND in patients with and without LF were 20% vs. 5% (p=0.005) and 47% vs. 6% (p=0.0001), respectively. The PT and ND volume regression rates for patients with and without LF were 12.7% per week vs. 15.9% per week (p=0.04) and 3.4% per week vs. 10.5% per week (p<0.001), respectively. Utilizing an EOT cut-off value of 25% residual volume, the relative risks of LF for PT and ND were 14.7 (p=0.03) and 25 (p=0.001), respectively. Patients found with PT and/or ND residual volumes <25% at EOT had longer 2year OS of 100% vs. 67% (p=0.0023) and PFS of 87% vs. 17% (p<0.001) compared with patients with residual volumes >/= 25% at EOT.

CONCLUSION

Patients with locally advanced HNSCC who have significant MVCT volume reduction over the course of definitive CRT tend to have favorable clinical outcomes.

Inter-Fraction Tumor Volume Response during Lung Stereotactic Body Radiation Therapy Correlated to Patient Variables

Purpose

Analyze inter-fraction volumetric changes of lung tumors treated with stereotactic body radiation therapy (SBRT) and determine if the volume changes during treatment can be predicted and thus considered in treatment planning.

Methods and Materials

Kilo-voltage cone-beam CT (kV-CBCT) images obtained immediately prior to each fraction were used to monitor inter-fraction volumetric changes of 15 consecutive patients (18 lung nodules) treated with lung SBRT at our institution (45–54 Gy in 3–5 fractions) in the year of 2011–2012. Spearman's (ρ) correlation and Spearman's partial correlation analysis was performed with respect to patient/tumor and treatment characteristics. Multiple hypothesis correction was performed using False Discovery Rate (FDR) and q-values were reported.

Results

All tumors studied experienced volume change during treatment. Tumor increased in volume by an average of 15% and regressed by an average of 11%. The overall volume increase during treatment is contained within the planning target volume (PTV) for all tumors. Larger tumors increased in volume more than smaller tumors during treatment (q = 0.0029). The volume increase on CBCT was correlated to the treatment planning gross target volume (GTV) as well as internal target volumes (ITV) (q = 0.0085 and q = 0.0039 respectively) and could be predicted for tumors with a GTV less than 22 mL. The volume increase was correlated to the integral dose (ID) in the ITV at every fraction (q = 0.0049). The peak inter-fraction volume occurred at an earlier fraction in younger patients (q = 0.0122).

Conclusions

We introduced a new analysis method to follow inter-fraction tumor volume changes and determined that the observed changes during lung SBRT treatment are correlated to the initial tumor volume, integral dose (ID), and patient age. Furthermore, the volume increase during treatment of tumors less than 22mL can be predicted during treatment planning. The volume increase remained significantly less than the overall PTV expansion, and radiation re-planning was therefore not required for the purpose of tumor control. The presence of the studied correlations suggests that the observed volumetric changes may reflect some underlying biologic process rather than random fluctuations.

Cone-beam CT-guided radiotherapy in the management of lung cancer: Diagnostic and therapeutic value

BACKGROUND

Recent studies have demonstrated an increase in the necessity of adaptive planning over the course of lung cancer radiation therapy (RT) treatment. In this study, we evaluated intrathoracic changes detected by cone-beam CT (CBCT) in lung cancer patients during RT.

METHODS AND MATERIALS

A total of 71 lung cancer patients treated with fractionated CBCT-guided RT were evaluated. Intrathoracic changes and plan adaptation priority (AP) scores were compared between small cell lung cancer (SCLC, n = 13) and non-small cell lung cancer (NSCLC, n = 58) patients.

RESULTS

The median cumulative radiation dose administered was 54 Gy (range 30-72 Gy) and the median fraction dose was 1.8 Gy (range 1.8-3.0 Gy). All patients were subjected to a CBCT scan at least weekly (range 1-5/week). We observed intrathoracic changes in 83 % of the patients over the course of RT [58 % (41/71) regression, 17 % (12/71) progression, 20 % (14/71) atelectasis, 25 % (18/71) pleural effusion, 13 % (9/71) infiltrative changes, and 10 % (7/71) anatomical shift]. Nearly half, 45 % (32/71), of the patients had one intrathoracic soft tissue change, 22.5 % (16/71) had two, and three or more changes were observed in 15.5 % (11/71) of the patients. Plan modifications were performed in 60 % (43/71) of the patients. Visual volume reduction did correlate with the number of CBCT scans acquired (r = 0.313, p = 0.046) and with the timing of chemotherapy administration (r = 0.385, p = 0.013).

CONCLUSION

Weekly CBCT monitoring provides an adaptation advantage in patients with lung cancer. In this study, the monitoring allowed for plan adaptations due to tumor volume changes and to other anatomical changes.

Adaptive radiotherapy for locally advanced non-small cell lung cancer, can we predict when and for whom?

BACKGROUND

Adaptive radiotherapy (ART) could be a tool to reduce toxicity and to facilitate dose escalation in stage III NSCLC. Our aim was to identify the most appropriate time and potential benefit of ART.

MATERIAL AND METHODS

We analyzed volume reduction and dosimetric consequences of 41 patients who were treated with concurrent (cCRT) (n = 21) or sequential (sCRT) chemoradiotherapy to a median dose of 70 Gy, 2 Gy/F. At every treatment fraction a cone-beam CT (CBCT) was performed. The gross tumor volume (GTV-T) was adapted (exclusion of lymph nodes) to create the GTV-T-F1. Every fifth fraction (F5-F30), the GTV-T-F1 was adapted on the CBCT to create a GTV-T-Fx. Dose volume histograms were recalculated for every GTV-T-Fx, enabling to create lookup tables to predict the theoretical dosimetric advantage on common lung dose constraints.

RESULTS

The average GTV reduction was 42.1% (range 4.0-69.3%); 50.1% and 33.7% for the cCRT and sCRT patients, respectively. A linear relationship between GTV-T-F1 volume and absolute volume decrease was found for both groups. The mean V5, V20, V30 and mean lung dose increased by 0.8, 3.1, 5.2 and 3.4%, respectively. A larger increase (p < 0.05) was observed for peripheral tumors and cCRT. Lookup tables were generated.

CONCLUSION

ART offers the most beneficial dosimetric effects when performed around fraction 15, especially for patients with a large initial GTV-T treated by cCRT.

The radiation techniques of tomotherapy & intensity-modulated radiation therapy applied to lung cancer

Radiotherapy (RT) plays an important role in the management of lung cancer. Development of radiation techniques is a possible way to improve the effect of RT by reducing toxicities through better sparing the surrounding normal tissues. This article will review the application of two forms of intensity-modulated radiation therapy (IMRT), fixed-field IMRT and helical tomotherapy (HT) in lung cancer, including dosimetric and clinical studies. The advantages and potential disadvantages of these two techniques are also discussed.

Tumor volume change with stereotactic body radiotherapy (SBRT) for early-stage lung cancer: evaluating the potential for adaptive SBRT

OBJECTIVES

To quantify gross tumor volume (GTV) change during stereotactic body radiotherapy (SBRT) and on first follow-up, as well as to evaluate for any predictive prognostic risk factors related to GTV decrease. An attempt was also made to identify the potential timing for adaptive SBRT.

METHODS

Twenty-five tumors in 24 consecutive patients were treated with SBRT to total dose of 50 Gy in 5 fractions. Median age was 72.5 years. Tumor stage was T1, 68%; T2, 20%; and other, 12%. The GTVs of on the 5 cone-beam computed tomographies (CBCT1-5) obtained before each fraction and the first follow-up CT (CTPOST) were analyzed.

RESULTS

Median time from diagnosis to initiation of radiotherapy was 64 days. GTV on CBCT1 was the baseline for comparison. GTV decreased by a mean of 7% on CBCT2 (P=0.148), 11% on CBCT3 (P=0.364), 19% on CBCT4 (P=0.0021), and 32% on CBCT5 (P=0.0004). Univariate analyses of GTV shrinkage was significantly associated with "time from CBCT5 to CTPOST" (P=0.027) and "T-stage" (P=0.002). In multivariate analyses, "T-stage" remained significant with T1 tumors showing greater GTV shrinkage than T2 tumors.

CONCLUSIONS

Significant decrease in GTV volume based on daily CBCT was demonstrated during SBRT treatment. Adaptive SBRT has the potential to minimize integral dose to the surrounding normal tissues without compromising GTV coverage.

Kinetic Models for Predicting Cervical Cancer Response to Radiation Therapy on Individual Basis Using Tumor Regression Measured In Vivo With Volumetric Imaging

This article describes a macroscopic mathematical modeling approach to capture the interplay between solid tumor evolution and cell damage during radiotherapy. Volume regression profiles of 15 patients with uterine cervical cancer were reconstructed from serial cone-beam computed tomography data sets, acquired for image-guided radiotherapy, and used for model parameter learning by means of a genetic-based optimization. Patients, diagnosed with either squamous cell carcinoma or adenocarcinoma, underwent different treatment modalities (image-guided radiotherapy and image-guided chemo-radiotherapy). The mean volume at the beginning of radiotherapy and the end of radiotherapy was on average 23.7 cm(3) (range: 12.7-44.4 cm(3)) and 8.6 cm(3) (range: 3.6-17.1 cm(3)), respectively. Two different tumor dynamics were taken into account in the model: the viable (active) and the necrotic cancer cells. However, according to the results of a preliminary volume regression analysis, we assumed a short dead cell resolving time and the model was simplified to the active tumor volume. Model learning was performed both on the complete patient cohort (cohort-based model learning) and on each single patient (patient-specific model learning). The fitting results (mean error: ∼ 16% and ∼ 6% for the cohort-based model and patient-specific model, respectively) highlighted the model ability to quantitatively reproduce tumor regression. Volume prediction errors of about 18% on average were obtained using cohort-based model computed on all but 1 patient at a time (leave-one-out technique). Finally, a sensitivity analysis was performed and the data uncertainty effects evaluated by simulating an average volume perturbation of about 1.5 cm(3) obtaining an error increase within 0.2%. In conclusion, we showed that simple time-continuous models can represent tumor regression curves both on a patient cohort and patient-specific basis; this discloses the opportunity in the future to exploit such models to predict how changes in the treatment schedule (number of fractions, doses, intervals among fractions) might affect the tumor regression on an individual basis.

Assessment of interpatient heterogeneity in tumor radiosensitivity for nonsmall cell lung cancer using tumor-volume variation data

PURPOSE

In our previous work, the authors showed that a distribution of cell surviving fractions S2 in a heterogeneous group of patients could be derived from tumor-volume variation curves during radiotherapy for head and neck cancer. In this research study, the authors show that this algorithm can be applied to other tumors, specifically in nonsmall cell lung cancer. This new application includes larger patient volumes and includes comparison of data sets obtained at independent institutions.

METHODS

Our analysis was based on two data sets of tumor-volume variation curves for heterogeneous groups of 17 patients treated for nonsmall cell lung cancer with conventional dose fractionation. The data sets were obtained previously at two independent institutions by using megavoltage computed tomography. Statistical distributions of cell surviving fractions S2 and clearance half-lives of lethally damaged cells T(1/2) have been reconstructed in each patient group by using a version of the two-level cell population model of tumor response and a simulated annealing algorithm. The reconstructed statistical distributions of the cell surviving fractions have been compared to the distributions measured using predictive assays in vitro.

RESULTS

Nonsmall cell lung cancer presents certain difficulties for modeling surviving fractions using tumor-volume variation curves because of relatively large fractional hypoxic volume, low gradient of tumor-volume response, and possible uncertainties due to breathing motion. Despite these difficulties, cell surviving fractions S2 for nonsmall cell lung cancer derived from tumor-volume variation measured at different institutions have similar probability density functions (PDFs) with mean values of 0.30 and 0.43 and standard deviations of 0.13 and 0.18, respectively. The PDFs for cell surviving fractions S2 reconstructed from tumor volume variation agree with the PDF measured in vitro.

CONCLUSIONS

The data obtained in this work, when taken together with the data obtained previously for head and neck cancer, suggests that the cell surviving fractions S2 can be reconstructed from the tumor volume variation curves measured during radiotherapy with conventional fractionation. The proposed method can be used for treatment evaluation and adaptation.

Novel multimodality segmentation using level sets and Jensen-Rényi divergence

PURPOSE

Positron emission tomography (PET) is playing an increasing role in radiotherapy treatment planning. However, despite progress, robust algorithms for PET and multimodal image segmentation are still lacking, especially if the algorithm were extended to image-guided and adaptive radiotherapy (IGART). This work presents a novel multimodality segmentation algorithm using the Jensen-Rényi divergence (JRD) to evolve the geometric level set contour. The algorithm offers improved noise tolerance which is particularly applicable to segmentation of regions found in PET and cone-beam computed tomography.

METHODS

A steepest gradient ascent optimization method is used in conjunction with the JRD and a level set active contour to iteratively evolve a contour to partition an image based on statistical divergence of the intensity histograms. The algorithm is evaluated using PET scans of pharyngolaryngeal squamous cell carcinoma with the corresponding histological reference. The multimodality extension of the algorithm is evaluated using 22 PET/CT scans of patients with lung carcinoma and a physical phantom scanned under varying image quality conditions.

RESULTS

The average concordance index (CI) of the JRD segmentation of the PET images was 0.56 with an average classification error of 65%. The segmentation of the lung carcinoma images had a maximum diameter relative error of 63%, 19.5%, and 14.8% when using CT, PET, and combined PET/CT images, respectively. The estimated maximal diameters of the gross tumor volume (GTV) showed a high correlation with the macroscopically determined maximal diameters, with a R(2) value of 0.85 and 0.88 using the PET and PET/CT images, respectively. Results from the physical phantom show that the JRD is more robust to image noise compared to mutual information and region growing.

CONCLUSIONS

The JRD has shown improved noise tolerance compared to mutual information for the purpose of PET image segmentation. Presented is a flexible framework for multimodal image segmentation that can incorporate a large number of inputs efficiently for IGART.

Strategies of dose escalation in the treatment of locally advanced non-small cell lung cancer: image guidance and beyond

Radiation dose in the setting of chemo-radiation for locally advanced non-small cell lung cancer (NSCLC) has been historically limited by the risk of normal tissue toxicity and this has been hypothesized to correlate with the poor results in regard to local tumor recurrences. Dose escalation, as a means to improve local control, with concurrent chemotherapy has been shown to be feasible with three-dimensional conformal radiotherapy in early phase studies with good clinical outcome. However, the potential superiority of moderate dose escalation to 74 Gy has not been shown in phase III randomized studies. In this review, the limitations in target volume definition in previous studies; and the factors that may be critical to safe dose escalation in the treatment of locally advanced NSCLC, such as respiratory motion management, image guidance, intensity modulation, FDG-positron emission tomography incorporation in the treatment planning process, and adaptive radiotherapy, are discussed. These factors, along with novel treatment approaches that have emerged in recent years, are proposed to warrant further investigation in future trials in a more comprehensive and integrated fashion.